Your team has surfaced irregularities in your finance reports. Sometimes they even find different totals reported across different financial reports. The data team has no confidence in the data pipelines supporting the finance reports, and no way to validate them. Often, this lack of confidence leads companies to hire a data engineer.
A data engineer builds confidence by creating reliable, effective systems that move data from its source to support reports and/or help build and develop company applications and/or products.
This guide explains how to hire a data engineer: define the role, identify essential skills, assess candidates fairly, and ask questions that reveal how they work when data gets messy.
There are many ways to define “data engineer.” It really depends on the company and/or team’s goals, and the support needed. Also, a myriad of tools can support a data engineer. Sometimes, a company can screen out the most qualified candidate by focusing on a narrow set of tools.
Role | Primary Responsibility | Typical Output |
Data Engineer | Makes data available, reliable, and usable | Pipelines, data models, documented datasets |
Data Analyst | Examines data to answer business questions | Dashboards, reports, recommendations |
Data Scientist | Develops statistical analyses or predictive models | Experiments, forecasts, models |
The roles overlap. An analyst may write transformations, while an engineer may investigate metrics. Hire according to the work that is currently stuck, not the title you used at another company.
Briefly bring together the hiring manager, an analyst, a software engineer and a representative from the security/governance team. Get their thoughts on what the main challenges in the role are and what successful work in the role looks like.
Write down:
Based on these constraints, what would success look like? From a candidate’s perspective, it paints a much clearer picture than requiring deep understanding and/or experience with 15-20 different technologies. It also gives a clearer indication of the type and level of work the role requires. Understanding the constraints helps answer these questions.
Once you understand the constraints, you can scope the role appropriately. A manager or senior leader should be able to coach and mentor team members, in addition to carrying out other tasks in the role (e.g., establishing and operating systems/processes, owning metrics and end-to-end business outcomes).
SQL is a core screening skill. A candidate should join tables correctly, handle missing or duplicate records, use window functions when appropriate and explain why a query returns a particular result.
Ask how they would design tables for orders, customers and refunds. Listen for grain, keys, historical changes, and the business meaning of each field. Good modeling saves trouble later.
Python is common, but the important skill is writing maintainable code. Look for clear functions, tests and logging. Look for sensible error handling and a plan for rerunning failed jobs without creating duplicate records.
Also, ask about incremental loads, pagination, rate limits, late-arriving data and changes to source schemas. Someone who has maintained a pipeline can usually explain an actual failure and how they prevented it from recurring.
Candidates should understand relational databases, warehouse or lake storage, file formats, partitioning and access controls. If you use a cloud provider, relevant experience helps.
Google Cloud’s data engineer certification scope covers designing processing systems, ingesting and storing data, preparing it for analysis and maintaining overall workloads. These are useful areas to assess regardless of your vendor.
A pipeline is valuable only if people can trust its output. Look for practical checks, including row counts, unique keys, accepted values, reconciliation against source systems, alerts for missing or stale data, etc.
Also, ask how the candidate would develop and execute a recovery plan if a time-sensitive job failed. They should know how to limit permissions, protect sensitive fields, and avoid putting credentials in code.
Your engineer should be able to ask which metric is wrong, trace the issue, explain the impact without jargon and agree on a fix with the people who use the data. Ask for examples of definition disagreements and how they resolved them.
Name the tools your new hire will use soon, then separate requirements from preferences. A practical list could look like this:
Category | Examples | What to Assess |
Querying and Code | SQL, Python | Can they write, review, and debug production work? |
Storage | PostgreSQL, Snowflake, BigQuery, Redshift | Do they understand tables, cost, performance, and access? |
Transformation | dbt, Spark, SQL-based jobs | Can they choose an approach that fits the workload? |
Orchestration | Airflow, managed schedulers | Can they manage dependencies, retries, and backfills? |
Ingestion and Streaming | Managed connectors, Kafka | Have they handled source changes and event timing? |
Delivery | Git, CI/CD, monitoring tools | Can they test, deploy, observe, and recover safely? |
Mark only the tools needed on day one as required. If your team uses Snowflake but the role mainly needs strong warehouse SQL, say so. Reserve platform-specific depth for a role that truly owns that platform.
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Job seekers want to know the work they’ll do and the impact it will have. Start your job description with this information. It is also important to provide details about the data infrastructure (i.e., your “data stack”) as it relates to the role.
Describe any on-call support responsibilities. Define the role’s geography and provide other relevant information, including employment type and compensation range. State the essential qualifications and any preferred qualifications.
Many resources can help people create a resume that includes specific keywords. A resume may look attractive, but it tells you little about the person and their experience. Evaluate the scale and complexity of the data systems the candidate has supported, along with their role in designing or improving those systems.
Assess the candidate’s business impact, including how they responded to failures and what improvements resulted from their actions. Also evaluate the candidate’s design decisions and trade-offs to understand the outcome they expected.
Ask candidates to write SQL queries that join sales and refund transaction data. Then, have them create a report and explain how they would enter and load data into the system. Evaluate their logic during a short, timed interview.
Make the evaluation of the candidate’s exercise as open as possible. Be clear that you will evaluate spelling and grammar. Be fair with your assessment of the candidate’s exercise. If you use a take-home exercise, keep the exercise short.
Discuss how to create a system to handle a daily report when the source systems are not under your control. The source systems may deliver data in inconsistent formats or at unpredictable times. Provide realistic constraints that allow the candidate to explain their design decisions.
An excellent candidate will make many appropriate assumptions and design the system to provide failover. Be sure the candidate takes an incremental design approach. The candidate should identify load and scheduling constraints and provide an appropriately detailed system design, describing trade-offs.
Evaluate all candidates against the same predefined criteria. Record your evaluation and rationale immediately after the interview. Use a scorecard to set acceptable ranges for each skill you evaluate.
Before interviews, agree on what will make a candidate “strong” in each evaluated skill.
1. How would you calculate monthly net revenue when orders can be refunded later?
Look for a clear definition of revenue, an approach to handling partial refunds, appropriate date selections and safeguards against double counting.
2. A join has doubled the number of rows in a report. How would you debug it?
Strong answers check the grain and uniqueness of each table, inspect join keys and compare row counts at each step.
3. How would you model customer history when an account changes its region?
Listen for whether reports need the current region or the region at the time of a transaction. The candidate should ask before choosing a design.
1. A nightly load failed after writing half its rows. How would you rerun it safely?
Look for idempotent writes, checkpoints or staging, deduplication and verification after recovery.
2. An API adds a field and changes another field’s type. What happens next?
Good answers mention detection, compatibility, tests, communication with consumers and a controlled migration.
3. How would you detect that a pipeline succeeded technically but produced incomplete data?
Expect freshness, volume, quality and source-to-target checks, not just a green scheduler status.
1. Tell us about a data incident you owned. What did you do first?
Seek a clear timeline: confirm impact, contain the issue, communicate, restore service and prevent recurrence. A candid account is more useful than a flawless story.
2. Two departments define “active customer” differently. How do you proceed?
Look for stakeholder discussion, documented definitions and deliberate naming of separate metrics if both are valid.
3. What would you improve first in our current data setup?
Good candidates ask questions, identify a manageable first step and avoid promising a complete rebuild without evidence.
Follow up with “Why?” and “What would change your approach?” These questions reveal how a candidate thinks far better than asking them to recite commands.
When hiring data engineers, prioritize candidates who can identify data challenges, build reliable systems and maintain data quality.
Trustworthiness encompasses a broad range of validity, reliability and security considerations, among others. To evaluate a candidate’s trustworthiness, ask for examples of the solution’s negatives or trade-offs. Other considerations can be the solution’s users or customers.
SPECTRAFORCE, as an established data engineer staffing agency, can help you find the data engineer you are looking for. Whether you want a full-time team member or a contract worker, we will help your hiring team with the right list of suitable candidates.
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