Senior Data Engineer

Core Responsibilities:

• Design, build, and maintain robust ETL/ELT pipelines.

• Develop and optimize data ingestion, transformation, and processing workflows.

• Ensure data reliability, performance, and scalability.

• Implement data quality, validation, and monitoring within pipelines.

• Support analytics, BI, and AI/ML use cases with trusted datasets.

Technical Skills:

• Strong expertise in SQL and performance tuning.

• Proficiency in Python, Spark, or Scala.

• Hands-on experience with Data Warehouses, Data Lakes, Lakehouse architectures.

• Hand-on experience with Cloud platforms (AWS, Azure, or GCP).

• Experience with orchestration tools (Airflow, Azure Data Factory, Dagster).

• Experience with streaming / real-time data (Kafka, event-driven pipelines).

• Familiarity with CI/CD, Git, and DevOps practices.

Data Architecture & Integration:

• Ability to work closely with Data Architects to implement target architectures.

• Experience integrating data from APIs, databases, files, and SaaS platforms.

• Understanding of data modeling and analytics-ready schemas.

Data Governance & Security:

• Awareness of data governance, data quality, and metadata practices.

• Experience implementing data access controls and security.

• Understanding of privacy and compliance requirements.

Leadership & Collaboration:

• Acts as a technical lead on data engineering initiatives.

• Mentors junior data engineers and reviews code.

• Strong collaboration with product, analytics, and business teams.

Experience:

• 5+ years of experience in data engineering, data platforms, or analytics engineering.

• Proven experience building and operating scalable, production-grade data pipelines.

• Experience working in complex, multi-source enterprise environments.

Education & Certifications:

• Bachelor’s degree in computer science, Engineering, or related field.

• Cloud or data engineering certifications are a plus.