Data Engineer

2–4 years of experience in data engineering, analytics engineering, or software engineering with a focus on data.
Strong SQL skills and familiarity with at least one programming language (e.g., Python, Java, or Scala).
Hands-on experience with modern data tools such as Databricks, Airflow, dbt, Spark, or Kafka.
Understanding of data modeling concepts, data warehousing, and ETL/ELT best practices.
Experience working with cloud-based data platforms (AWS, GCP, or Azure).

Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
Write clean, efficient, and well-documented code using tools like Python, SQL, and Spark.
Ensure data is reliable, accurate, and delivered in a timely manner.
Work with data analysts, data scientists, and product managers to understand requirements and deliver actionable data solutions.
Translate business questions into engineering tasks and contribute to technical planning.
Participate in code reviews, sprint planning, and retrospectives as part of an agile team.
Monitor data pipelines and troubleshoot issues in a timely, systematic manner.
Implement data quality checks and contribute to observability and testing practices.
Document data sources, transformations, and architecture decisions to support long-term maintainability.

Experience supporting BI, analytics, or data science teams.
Familiarity with version control, CI/CD, and collaborative development workflows.
Exposure to data governance, privacy, or compliance practices.
Eagerness to learn new technologies and contribute to the growth of the team.