Data Engineer

Responsibilities

• Design, build, and maintain scalable data pipelines and processing workflows that support reliable access to business-critical data.
• Develop reusable data platforms and automation solutions that improve the efficiency, consistency, and performance of data operations.
• Produce clear, maintainable, and well-documented code for data integration, transformation, and platform services.
• Establish automated validation and testing practices to monitor accuracy, completeness, and overall data quality.
• Partner with architects, product leaders, data scientists, and DevOps teams to deliver resilient data systems aligned with technical and business goals.
• Assess new data sources, determine their value and fit, and implement effective ingestion approaches.
• Deploy and integrate data management capabilities within enterprise or client environments while meeting operational requirements.
• Strengthen data protection and continuity by identifying risks, supporting backup strategies, and contributing to recovery planning.
• Build and support data storage solutions such as warehouses, lakes, and operational repositories for reporting and advanced analytics.

Requirements

• At least 7 years of experience in data engineering or a closely related technical discipline.
• Demonstrated success building large-scale, production-ready data pipelines and data processing solutions.
• Strong programming skills in Python and solid experience with SQL and workflow orchestration tools such as Airflow and dbt.
• Hands-on experience with Databricks in a cloud environment, including pipeline development, distributed processing, and performance tuning.
• Practical knowledge of big data technologies such as Apache Spark, Kafka, and Hadoop, along with modern data formats including Parquet, Delta Lake, or Iceberg.
• Experience working with cloud data services and platforms such as object storage, managed ETL tools, analytical databases, or comparable Azure and Google Cloud offerings.
• Solid understanding of data modeling, secure data architecture, and optimization techniques for high-performing data stores.
• Ability to collaborate effectively in Agile teams and communicate clearly with both technical stakeholders and business partners.