Job Summary
We are seeking a highly skilled Data Engineer Supervisor to lead the design, development, and optimization of scalable data platforms and pipelines. This role combines hands-on technical expertise with team leadership, ensuring the delivery of high-quality, reliable, and secure data solutions. The ideal candidate will supervise data engineers, drive architectural decisions, and collaborate closely with analytics, data science, and business teams.
Key Responsibilities
Technical & Architecture
- Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data processing.
- Architect and manage data lakes, data warehouses, and streaming solutions.
- Develop and optimize data models to ensure performance, scalability, and usability.
- Ensure data quality, validation, lineage, governance, and documentation across platforms.
- Implement data security, access controls, and compliance best practices.
- Optimize performance of distributed data processing systems.
- Develop automation, monitoring, and alerting for data workflows.
- Work with DevOps teams to deploy and manage data workloads in cloud environments.
Leadership & Supervision
- coach data engineering team members.
- Conduct code reviews and ensure adherence to engineering standards and best practices.
- Support team capacity planning, task prioritization, and delivery timelines.
- Contribute to technical roadmaps and architectural decisions.
- Act as a technical point of escalation for complex data issues.
- Collaborate with stakeholders to translate business requirements into technical solutions.
Required Skills & Experience
- 5+ years of hands-on experience in Data Engineering.
- 1–3 years experience in a lead or supervisory role (preferred).
- Strong programming experience with Python, Scala, or Java.
- Advanced proficiency in SQL and working with large-scale datasets.
- Experience with big data and orchestration tools such as:
- Apache Spark, Hadoop, Kafka, Flink, Airflow, dbt.
- Cloud experience with at least one platform:
- AWS (Glue, EMR, Redshift, Athena, S3)
- Azure (Data Factory, Synapse, Databricks)
- GCP (BigQuery, Dataflow, Dataproc)
- Experience with modern data warehouses:
- Snowflake, Redshift, BigQuery, Synapse, etc.
- Knowledge of CI/CD pipelines, Git, Terraform, Docker, and/or Kubernetes.
- Strong understanding of data modeling, dimensional modeling, and schema design.
