Description

Architect, build, and maintain scalable data pipelines, ETL processes, and data models for structured and unstructured sources.

This role is on-site.

Responsibilities

• Design and deploy data ingestion frameworks and scalable pipelines using cloud technologies.
• Optimize performance for large-scale data lakes and warehouses, ensuring efficient query execution.
• Implement data governance, lineage, and quality frameworks to maintain data integrity.
• Mentor junior data engineers and enforce best practices in data engineering and code quality.
• Collaborate with data scientists, analysts, and DevOps teams to ensure seamless integrations.

Required Skills

• 8+ years of hands-on experience in data engineering, ETL development, and pipeline automation.
• Strong expertise in at least one major cloud platform: AWS, Azure, or GCP.
• Proficiency with Spark, PySpark, Databricks, Kafka, Snowflake, Airflow, SQL, and Python.
• Experience with data warehousing solutions such as Redshift, BigQuery, or Synapse.
• Solid understanding of data modeling, orchestration, streaming technologies, and performance tuning.
• Bachelor's degree in Computer Science or a related field.

Preferred Skills

• Experience leading data modernization or migration projects.
• Familiarity with CI/CD pipelines and containerization (Docker/Kubernetes).

Key Skills

Education

Bachelor's degree