About the Data Engineer role
A Data Engineer builds and maintains the infrastructure that moves data through a company. They design pipelines that ingest data from applications, APIs, and third-party sources, transform it into usable shape, and load it into warehouses or lakes where analysts, scientists, and applications can rely on it.
The role is closer to software engineering than to analysis. A strong data engineer writes production-grade code, thinks about reliability and cost, and treats data quality as an engineering problem with tests, monitoring, and alerts. In many companies, data engineers also own the data platform itself: orchestration, warehouse performance, access controls, and the tooling other data roles depend on.
In your posting, name your warehouse, orchestration tool, and cloud provider, and describe the scale of data involved. State whether the engineer will build pipelines for analytics, power customer-facing features, or both. Candidates evaluate data engineering roles largely on the maturity of the stack.
Data Engineer job description template
Job brief
We are looking for a Data Engineer to design, build, and maintain the data pipelines and infrastructure that power our analytics and products. You will develop reliable ETL and ELT workflows, model data in our warehouse, and work with analysts, data scientists, and software engineers to make trustworthy data available across the company. To succeed in this role, you should combine strong SQL and programming skills with a software engineering mindset around testing, monitoring, and scalability.
Responsibilities
- Design, build, and maintain scalable ETL and ELT pipelines from internal and external data sources
- Model, document, and optimize datasets in the data warehouse for analytics and product use
- Write clean, tested, production-grade code for data ingestion and transformation
- Monitor pipeline health and data quality, and resolve failures and anomalies quickly
- Optimize warehouse performance and manage storage and compute costs
- Implement data validation, testing, and observability across pipelines
- Collaborate with analysts and data scientists to understand data needs and deliver reliable datasets
- Manage data access, security, and compliance requirements with the platform team
- Evaluate and integrate new tools that improve the data platform
Requirements and skills
- Proven working experience as a Data Engineer or in a similar data infrastructure role
- Strong SQL skills, including query optimization on large datasets
- Proficiency in Python or another language commonly used for data pipelines
- Hands-on experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift
- Experience with an orchestration tool such as Airflow, Dagster, or Prefect
- Solid understanding of data modeling concepts such as dimensional modeling and slowly changing dimensions
- Familiarity with at least one major cloud platform such as AWS, GCP, or Azure
- BSc in Computer Science, Engineering, or a related field, or equivalent experience
Nice to have
- Experience with dbt and modern ELT workflows
- Experience with streaming technologies such as Kafka or Kinesis
- Familiarity with Spark or other distributed processing frameworks
- Experience with infrastructure as code tools such as Terraform
- Exposure to data governance, cataloging, or privacy tooling
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