{"id":1252995,"url":"https://alion.io/job/a-services-company-data-engineer","title":"Data Engineer","company":{"id":3800646,"name":"A Services company","domain":"spectrumconsultingindia.com","url":"https://alion.io/company/a-services-company","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India","Bengaluru, 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scalable data pipelines for analytical and BI workloads.\n\nThe ideal candidate brings hands-on expertise in PySpark, Delta Lake, and cloud-native integration between AWS and Databricks.\n\nKey Responsibilities :\n\n- Develop and maintain batch and streaming ETL/ELT data pipelines using Databricks and PySpark on AWS.\n\n- Implement Lakehouse architectures using Delta Lake on Amazon S3 following the Medallion architecture (Bronze/Silver/Gold).\n\n- Orchestrate data workflows using Databricks Workflows, AWS Step Functions, or Apache Airflow (MWAA).\n\n- Write, tune, and optimize complex SQL queries for Amazon Redshift, Athena, and Databricks SQL.\n\n- Configure secure data ingestion, storage, and cataloging leveraging AWS IAM, S3, and Databricks Unity Catalog.\n\n- Build automated data validation checks and unit tests to ensure high data quality and pipeline reliability.\n\n- Implement CI/CD deployment workflows using Git, Databricks Asset Bundles (DABs), or AWS CI/CD tools.\n\n- Collaborate with data analysts, data scientists, and downstream stakeholders to deliver performant data models.\n\nTechnical Skills Required :\n\n- Big Data & Compute: Databricks, Apache Spark, PySpark, Delta Lake\n\n- AWS Services: Amazon S3, Redshift, Athena, IAM, CloudWatch\n\n- Programming & Querying: Python, PySpark, Advanced SQL\n\n- Orchestration: Databricks Workflows, Apache Airflow, or AWS Step Functions\n\n- Streaming & Messaging: Apache Kafka, AWS Kinesis, or Spark Structured Streaming\n\n- Data Governance & Formats: Unity Catalog, Parquet, Delta format\n\n- Version Control & DevOps: Git, GitHub/GitLab, Docker basics\n\nGood to Have :\n\n- Databricks Certified Data Engineer Associate/Professional certification.\n\n- Familiarity with AWS Glue, EMR, or DynamoDB.\n\n- Experience with dbt (data build tool) for SQL transformations.\n\n- Exposure to Generative AI integration, vector databases, or AWS Bedrock.\nSkills\nDatabricks, PySpark, Delta Lake, AWS, Python, SQL, Apache 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