Lead/Senior Data Engineer

Lead/Senior Data Engineer

Experience: 6 to 8 years
Employment Type: Full-time

About the Role

We are looking for an experienced Senior Data Engineer to design, build, and maintain scalable data platforms and pipelines. You will work across batch and streaming workloads, data lakes/warehouses, orchestration, and data quality while partnering closely with business and technical stakeholders.

Key Responsibilities

• Design, develop, and maintain robust, scalable ETL/ELT pipelines for batch and streaming data.
• Build and manage data lake and data warehouse architectures optimized for performance, reliability, and cost.
• Develop and orchestrate data workflows using modern orchestration tools such as Airflow or Dagster.
• Ensure data quality, integrity, governance, and reliability across pipelines and platforms.
• Optimize SQL queries, storage layouts, and data processing jobs for performance at scale.
• Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable solutions.
• Drive best practices around data modeling, schema design, testing, documentation, and version control.
• Troubleshoot and improve data pipelines to ensure high availability and operational reliability.

Required Skills & Experience

• 610 years of experience in data engineering, with a strong foundation in distributed data systems.
• Strong hands-on expertise in SQL/PostgreSQL and Python for data processing and pipeline development.
• Experience with workflow orchestration tools such as Apache Airflow, Dagster, or similar.
• Strong working knowledge of AWS data services, particularly Amazon S3 and AWS Glue.
• Familiarity with streaming technologies such as Apache Kafka, Amazon Kinesis, or Spark Structured Streaming.
• Experience with data modeling, schema design, and scalable data processing architectures.
• Strong understanding of data quality, reliability, and pipeline monitoring.
• Excellent problem-solving and communication skills.

Good to Have

• Experience with dbt and modern transformation workflows.
• Experience with data quality and observability tools.
• Knowledge of Docker and Kubernetes.
• Understanding of data security, compliance, and governance frameworks.
• Experience working with CI/CD and infrastructure-as-code practices.

What You'll Bring

• A strong engineering mindset with a focus on building reliable, scalable systems.
• Ability to work independently while collaborating effectively with cross-functional teams.
• Strong ownership of data platforms and a commitment to engineering best practices.
• Curiosity and willingness to learn and adopt modern data technologies.