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If you’ve Googled “Data Engineer job description,” you’ve probably seen the same thing over and over:
Bullet points. Buzzwords. Boring copy.
But here’s the truth: most of these templates don’t actually help you attract a great data engineer—they just help you publish a job post.
And in a competitive hiring market, that’s not enough.
Top data engineers aren’t just looking for a paycheck. They want meaningful work, a collaborative team, and a company that takes engineering seriously.
So if your job description is generic and lifeless, you won’t attract the kind of talent who can truly build your data infrastructure.
In this guide, we’re going to do things differently.
We’ll show you:
- What a great Data Engineer job post actually looks like
- Why most templates fail to attract top applicants
- Two real job description templates you can copy and tailor
- Extra tips that help you stand out—and hire better
Before we dive in, if you haven’t already, check out our master guide on full guide on how to write a job post that attracts top talent: Link https://workscreen.io/how-to-write-a-job-post/ so you understand the proven structure that top-performing companies use to stand out in hiring.
Ready? Let’s break it down.
WorkScreen simplifies the hiring process, helping you quickly identify top talent while eliminating low-quality applications. By saving you countless hours and reducing the risk of bad hires, it empowers you to build a team that delivers results
What A Data Engineer Actually Does (Their Duties)
So, what does a Data Engineer actually do?
A Data Engineer is the person who builds and maintains the pipelines that move, clean, and organize data so it can be used by analysts, scientists, and decision-makers. Think of them as the builders behind your company’s data infrastructure.
They don’t just move data—they make sure it’s accessible, reliable, and usable.
They create systems that help everyone from product managers to CFOs make better decisions—faster. Whether it’s streaming real-time user behavior or structuring massive internal databases, the Data Engineer is the unsung hero who ensures everything runs smoothly behind the scenes.
And because this role sits at the intersection of engineering, analytics, and operations, you’re not just hiring for technical skill—you’re hiring for clarity, ownership, and long-term thinking.
The bottom line? If you want your business to make smarter, data-driven decisions, you need a great Data Engineer. And that starts with a job description that reflects just how important the role is.
Two Great Data Engineer Job Description Templates
Option 1: For Experienced Candidates
Job Title: Senior Data Engineer at Lumina Health
Location: Remote (US-Based)
Type: Full-Time | 
Flexible Hours
Salary: $120,000–$145,000 + Equity
Reports To: Director of Engineering
[Meet Our Hiring Manager – [Insert Loom Video from Hiring Manager]
Who We Are
At Lumina Health, we’re building tools that help patients access care faster—and that starts with better data. Our platform connects clinics, insurance providers, and patients through real-time data integrations.
We’re a team of builders, designers, and healthcare nerds. And right now, we’re looking for a seasoned Data Engineer who’s passionate about building scalable data systems that power real-world decisions.
What You’ll Be Doing
As our Senior Data Engineer, you’ll lead the design and development of our modern data stack. You’ll help us move from messy, siloed datasets to clean, real-time pipelines that drive insights across the company.
Specifically, you’ll:
- Build and optimize ETL/ELT workflows using tools like Airflow, dbt, and Fivetran
- Design and maintain data warehouses in Snowflake
- Create and maintain data models that support internal analytics and product features
- Partner with analysts, data scientists, and engineers to understand data needs
- Ensure data governance, quality, and compliance across systems
What We’re Looking For
- 3+ years of experience in data engineering
- Strong SQL skills and experience with Python
- Familiarity with modern data tools (Airflow, dbt, Snowflake, etc.)
- Experience working with APIs, event streams, or real-time data
- Clear communicator who can explain technical topics to non-technical stakeholders
Bonus if you’ve worked in healthcare or with HIPAA-compliant systems—but not required.
Why You’ll Love Working Here
We move fast, keep things real, and genuinely care about each other.
We offer:
- Competitive salary and equity
- 100% remote setup with flexible hours
- Health, dental, and vision insurance
- 20+ days paid time off + company-wide recharge weeks
- Learning stipend and career development budget
Our Hiring Process
We use WorkScreen to ensure a fair, skills-based evaluation process. You’ll complete a short, relevant challenge to show how you think. Then we’ll chat, get to know each other, and walk you through the team, culture, and role. Every applicant gets a response.
Apply here: [Workscreen application link]
Option 2: For Entry-Level or Trainable Candidates
Job Title: Junior Data Engineer (We’ll Train You)
Location: Hybrid (Austin, TX)
Type: Full-Time | Entry-Level
Salary: $65,000–$75,000 + Benefits
Reports To: Lead Data Engineer
Meet Your Team
We know applying to a new job can feel intimidating—so we made a quick video to show you who you’ll be working with, what we’re building, and why this role matters.
[Insert Loom or YouTube link here]
About the Role
We’re looking for someone who’s curious about data, loves solving problems, and wants to grow into a Data Engineer role. You don’t need years of experience—we’ll teach you what you need to know.
If you’re familiar with spreadsheets, have played around with SQL, or built simple automations—you might be a great fit.
What You’ll Be Doing
- Support the data team in building and maintaining ETL processes
- Help clean, validate, and structure raw datasets
- Build simple scripts in Python or SQL (we’ll guide you)
- Document processes and support the analytics team
- Learn modern tools like dbt, BigQuery, and Fivetran
What We’re Looking For
- Passion for data and learning new tools
- Strong attention to detail
- Some experience with Excel, SQL, Python—or a willingness to learn fast
- Clear communicator and team player
We care more about your mindset than your resume. If you’re ready to learn and grow, we want to hear from you.
Why Work With Us
- Full training and mentorship from senior engineers
- Hands-on experience with real projects
- Paid certifications and learning support
- Health benefits and PTO
- Clear promotion path within 12–18 months
How to Apply
We use WorkScreen to evaluate candidates based on potential and learning ability. Apply using the link below—no resume required.
Apply here: [Workscreen application link]
Build a winning team—without the hiring headache. WorkScreen helps you hire fast, confidently, and without second-guessing.
Why These Data Engineer Job Posts Work
Let’s break down why both of these job descriptions stand out—and how they’re designed to attract the right talent (not just more applicants).
1. The Job Titles Are Clear and Specific
They don’t just say “Data Engineer” or “Hiring Now.”
Instead:
- “Senior Data Engineer at Lumina Health” instantly communicates level, function, and company context.
- “Junior Data Engineer (We’ll Train You)” speaks directly to someone without experience and lowers the barrier to entry.
These titles filter in the right candidates—and filter out the wrong ones—before they even click.
2. Each Post Starts with a Warm, Human Introduction
Instead of jumping into dry bullet points, both posts open with context:
- What the company does
- Why this role matters
- What kind of people they’re looking for
This human tone builds trust—and makes the post feel like a conversation, not a contract.
3. They Include a Video From the Team
Adding a Loom or YouTube video gives the job post a face. It’s not just a company talking about a role—it’s a person showing up to say, “Here’s who we are.”
Candidates who watch these are more likely to feel connected—and more likely to apply.
4. The Responsibilities Are Framed Around Impact
Instead of listing tasks like “write SQL queries,” the posts explain why those tasks matter:
“You’ll help us move from messy, siloed datasets to clean, real-time pipelines that drive insights.”
That kind of framing helps candidates visualize their contribution and feel excited about the work.
5. They’re Transparent About Salary and Perks
Both templates list:
- Salary range
- Work type (remote, hybrid)
- Benefits and perks
Transparency builds trust and sets expectations. It also filters out applicants who aren’t aligned—saving everyone time.
6. They Highlight Culture and Career Growth
Each post includes clear, authentic messaging about:
- Team values
- Growth opportunities
- How new hires are treated
The junior-level post especially emphasizes support, learning, and internal mobility—making it attractive to driven early-career talent.
7. They Explain the Hiring Process
Instead of “Only shortlisted candidates will be contacted,” these posts:
- Outline the use of WorkScreen
- Set expectations about skill evaluations
- Reassure applicants they’ll hear back
This is a small detail—but it dramatically improves candidate experience and increases trust in your brand.
Bad Data Engineer Job Description Example
Job Title: Data Engineer
Company: ABC Tech Group
Location: New York, NY
Job Type: Full-Time
Salary: Competitive
Job Summary
We are seeking a Data Engineer to join our growing team. The successful candidate will be responsible for designing and implementing data solutions to support business needs.
Responsibilities
- Build data pipelines
- Write ETL processes
- Work with stakeholders to gather requirements
- Maintain databases and ensure data accuracy
Requirements
- Bachelor’s degree in Computer Science or related field
- 2–4 years of data engineering experience
- Proficiency in SQL and Python
- Familiarity with cloud platforms
How to Apply
Submit your resume and cover letter to hr@abctech.com. Only shortlisted candidates will be contacted.
Why This Job Post Fails
1. The Job Title Is Too Generic
Just “Data Engineer”? That’s vague.
No mention of seniority, company mission, or even industry.
It doesn’t help the right candidate self-identify or get excited.
2. There’s No Personality or Context
The intro feels like it was copy-pasted from a job board.
No explanation of what the company does, who they’re serving, or what makes this role exciting.
Candidates don’t want to apply to a robot. They want to work with people and purpose.
3. No Salary Transparency
“Competitive” means nothing—and often turns people off.
Top talent wants clarity and honesty, not vague placeholders.
4. The Responsibilities Are Too Broad
“Build data pipelines.”
“Maintain databases.”
These are vague tasks with no context or measurable outcomes. Candidates can’t visualize their day-to-day work or the value they’d be adding.
5. Culture and Growth Are Missing
There’s no mention of:
- Company culture
- Learning opportunities
- What it’s like to work there
- Why someone would want to stay long-term
It feels like the company is checking boxes, not recruiting a team member.
6. The Hiring Process Feels Cold
“Only shortlisted candidates will be contacted” is a classic red flag.
It makes the company sound unapproachable—and discourages qualified candidates from applying.
7. Zero Call-to-Action Energy
There’s no invitation, no excitement, no humanity.
It ends with a cold upload instruction and no effort to build a relationship with the candidate.
Bonus Tips to Make Your Job Description Stand Out
Even if your structure is solid, a few thoughtful touches can dramatically increase the number of qualified, engaged, and excited applicants. Here are some details top companies add that make a big difference:
1. Add a Security & Privacy Disclaimer
Job seekers are increasingly wary of scams and phishing attempts. Including a short statement in your job post can build trust and show that you’re a legitimate, applicant-first employer.
Example:
“We take your privacy seriously. We’ll never ask for payment, bank details, or personal financial information during the hiring process.”
2. Mention Paid Leave or Flex Time
Many candidates value time off just as much as salary—especially remote or hybrid workers. Listing this upfront signals that you care about balance and well-being.
Example:
“Enjoy up to 20 days of paid time off per year, plus company-wide recharge weeks to rest, reflect, and return energized.”
3. Highlight Training & Growth Opportunities
Top applicants don’t just want a job—they want a path.
Show that your company invests in their growth.
Example:
“We offer a $1,000/year learning stipend, mentorship from senior engineers, and a clear promotion track. Your growth matters to us.”
4. Embed a Video From the Hiring Manager
We mentioned this earlier—but it’s worth repeating. A short Loom or YouTube video from the hiring manager or team lead can dramatically improve engagement.
Why it works:
- Makes the company feel real and approachable
- Builds early trust
- Gives insight into team culture and energy
Example:
Before you apply, take 60 seconds to meet our CTO. Here’s what we’re building and why we’re excited about it.
Here is an example that we used in our master guide on how to write a great job post description , you can check it out here https://www.loom.com/share/ba401b65b7f943b68a91fc6b04a62ad4
These simple tweaks can elevate a “pretty good” job post into something memorable—and that’s what it takes to attract the best candidates in a noisy hiring market.
5. Make the Call to Action Human and Encouraging
Don’t just say “Apply Now.” Invite them to take the next step with warmth.
Example:
“If this sounds like a fit, we’d love to hear from you. We take every application seriously and use WorkScreen to make sure great candidates don’t get lost in the shuffle.”
6. Show What Happens After They Apply
Candidates hate sending applications into a black hole. Set clear expectations and show you respect their time.
Example:
“You’ll receive a confirmation email as soon as you apply. Within 7–10 business days, we’ll review your submission and let you know next steps—no ghosting, ever.”
Should You Use AI to Write Job Descriptions?
AI can be a powerful tool for writing job descriptions—but only if you use it intentionally.
Lately, more and more platforms (including some ATS tools) offer “one-click” AI-generated job posts. And while that sounds convenient, it often leads to bland, generic content that doesn’t attract the right candidates.
Why You Shouldn’t Rely on AI Alone
Using AI without context leads to:
- Dry, soulless job posts that feel like they were written by robots—for robots
- Misaligned candidates, because the tone and expectations aren’t clear
- Brand damage, since the job post may not reflect your real team, values, or mission
Remember: a job description is your first impression. If it feels cold, generic, or outdated—you’ll lose great applicants before you even meet them.
The Right Way to Use AI: Be the Brain, Let It Be the Brush
AI is not the writer—you are.
Use it to shape, polish, and structure your ideas, not generate them from scratch.
Here’s a smarter approach:
Step 1: Feed AI the Raw Ingredients
Provide real details like:
- What your company does and who it serves
- What the role actually involves day-to-day
- What kind of culture you offer
- What kind of person would thrive in the role
- Salary range, location, and benefits
- The tone you want (conversational? mission-driven? fun?)
Step 2: Use a Prompt Like This:
“Help me write a job description for a [Job Title] at [Company Name]. We’re hiring someone to [Explain what the role does and why it matters]. Our culture is [Describe your values, pace, tone], and we want to attract people who [List qualities or experience you’re looking for].
Here are the benefits: [Insert perks].
Please use a friendly, human tone and include a warm intro, what the candidate will do, required skills, and how we hire. Here are some rough notes to guide you: [Paste your notes or ideas].”
Bonus Tip:
Point to a job description you like (even one of the examples from earlier in this guide) and say:
“I want something similar in style to this one—warm, specific, and easy to read.”
Treat AI like a writing assistant—not a shortcut.
Because the best candidates will notice the difference.
Don’t let bad hires slow you down. WorkScreen helps you find the right people—fast, easy, and stress-free.
Need a Quick Copy-Paste Job Description?
Option 1: Conversational, Culture-First Job Description Template
Job Title: [Role Title]
Location: [City / Remote]
Type: [Full-Time / Part-Time]
Salary: [$X–$Y Range]
Reports To: [Hiring Manager Title]
[Insert team/hiring manager Loom video link]
About Us
At [Company Name], we’re [briefly explain your mission in human terms]. Whether it’s [impact statement] or [who your customers are], we’re a team that’s obsessed with doing meaningful work—together.
Now we’re looking for a [Job Title] who’s excited to help us [big-picture goal or impact]. If you’re someone who thrives on [value traits: solving problems, building systems, working with purpose]—we’d love to meet you.
What You’ll Be Doing
In this role, you’ll:
- [Responsibility #1 with purpose]
- [Responsibility #2 with tools/tech]
- [Responsibility #3 showing collaboration]
- [Responsibility #4, real-world impact]
What We’re Looking For
You don’t need to check every box—but here’s what would help you thrive:
- [Key skill or experience]
- [Trait: e.g. detail-oriented, proactive]
- [Tool/language knowledge]
- [Optional: “Bonus if you have experience in…”]
Why You’ll Love Working Here
At [Company Name], we:
- [Highlight key cultural trait]
- [List top 2–3 benefits/perks: e.g. flexible hours, remote-first, paid learning budget]
- [Mention how you support growth or autonomy]
We don’t just hire for skills—we hire for alignment, ownership, and people we actually want to work with every day.
How We Hire
We use [WorkScreen.io] to make sure our hiring process is fast, fair, and skill-based. Once you apply, you’ll receive a confirmation and go through a quick evaluation to help us understand how you think and work.
Apply here: [Insert WorkScreen application link]
Option 2: Structured “Job Brief + Responsibilities + Requirements” Format
Job Title: [e.g. Data Engineer]
Location: [Remote / Onsite]
Type: Full-Time
Salary: [$X–$Y]
Reports To: [e.g. Director of Data]
Job Brief
We’re hiring a [Job Title] to help us [1–2 sentence summary of the role and impact]. You’ll work closely with [teams you’ll collaborate with] and help us [key goal, e.g. scale our data infrastructure / improve reporting / build smarter systems].
Responsibilities
- [Responsibility 1]
- [Responsibility 2]
- [Responsibility 3]
- [Responsibility 4]
Requirements
- [Skill or experience 1]
- [Skill or experience 2]
- [Familiarity with tools]
- [Optional: Degree or certification]
Bonus if you’ve worked with [industry, tool, or relevant experience]—but not required.
Perks & Benefits
- [Health insurance, dental, etc.]
- [Flexible time off policy]
- [Remote setup or learning stipend]
- [Team offsites / culture perks]
Application Process
We use WorkScreen.io to evaluate applicants based on real skills—not just resumes. Apply below to get started—we respect your time and keep you updated at every step.
Apply here: [Insert WorkScreen application link]
Let WorkScreen Handle the Next Step
You’ve now got a strong, compelling job description.
But writing the post is just the beginning.
The next challenge? Sorting through dozens (or hundreds) of applicants to find the few who can actually do the job. And that’s where most teams waste hours—reading resumes, chasing interviews, and second-guessing who to move forward.
That’s why we built WorkScreen.io.
✅ Here’s how WorkScreen helps you hire smarter:
● Quickly spot your top candidates
Once your job post is live, WorkScreen automatically evaluates applicants, ranks them on a performance-based leaderboard, and highlights the strongest fits—so you don’t have to dig through every résumé.
● Skill tests in one click
No more guesswork. With WorkScreen, you can assess candidates based on real-world tasks and role-specific challenges—not just experience or degrees.
● Filter out low-effort applicants
Tired of copy-paste applications and AI-generated cover letters? WorkScreen screens for effort and filters out those who don’t take the process seriously—so you only engage with people who actually want the job.
● Fair and modern candidate experience
From custom video questions to automated follow-ups, WorkScreen gives every applicant a clear, professional experience—while saving you hours in the process.
Smart hiring starts with great job posts— But it ends with a clear, fast, and fair evaluation process. Let WorkScreen take it from here.
FAQ
A strong Data Engineer typically brings a mix of technical and analytical skills. Core skills include:
- SQL (must-have for querying databases)
- Python (often used for data pipelines and automation)
- Data modeling and warehousing (e.g. working with Snowflake, BigQuery, Redshift)
- ETL/ELT tools (like dbt, Airflow, Fivetran)
- APIs and real-time data processing
- Cloud platforms (AWS, GCP, or Azure)
- Soft skills like problem-solving, clear communication, and collaboration with cross-functional teams are just as important.
In most cases, yes—at least basic coding skills are essential.
Data Engineers don’t need to be full-stack developers, but they do need to write efficient, maintainable code—typically in Python, SQL, or sometimes Scala or Java. Even with no-code and low-code tools becoming more popular, those platforms still require underlying logic and custom scripting for more advanced data transformations.
That said, for junior roles or internal tooling projects, you can absolutely hire someone who’s still learning—as long as they’re coachable and eager to grow.
As of 2025, average base salaries for Data Engineers in the U.S. vary based on experience, location, and company type:
- Entry-Level: $70,000–$90,000/year
- Mid-Level (2–5 years): $100,000–$130,000/year
- Senior-Level: $135,000–$160,000+
- Remote roles with specialized skills (e.g. real-time streaming, healthcare, compliance): up to $180,000+
Keep in mind: competitive salaries combined with growth opportunities and flexible work culture are what attract top-tier engineers—not just the paycheck.
A Data Engineer builds and maintains the infrastructure that makes clean, usable data available across the business.
A Data Scientist, on the other hand, uses that data to build models, forecast trends, and inform decisions.
In short: Data Engineers enable data. Data Scientists analyze it.
Both roles are essential—but require very different skill sets.
Traditional résumés and interviews only tell part of the story.
To evaluate real-world skills:
- Use a skills-based assessment platform like WorkScreen.io
- Give a short, role-relevant task (e.g. building a basic pipeline or optimizing a query)
- Include a brief written or video explanation to understand their thinking
This helps you gauge not just what they know—but how they solve problems, communicate, and approach their work.
