Job
Description
Job Summary: We are looking for a highly skilled Senior AWS Data Engineer to design, develop, and lead enterprise-grade data solutions on the AWS cloud. This position requires a blend of deep AWS technical proficiency, hands-on PySpark experience, and the ability to engage with business stakeholders in solution design. The ideal candidate will build scalable, secure, and high-performance data platforms using AWS-native tools and best practices. Role & responsibilities: Design and implement scalable AWS cloud-native data architectures, including data lakes, warehouses, and streaming pipelines Develop ETL/ELT pipelines using AWS Glue (PySpark/Scala), Lambda, and Step Functions Optimize Redshift-based data warehouses including schema design, data distribution, and materialized views Leverage Athena, Glue Data Catalog, and S3 for efficient serverless query patterns Implement IAM-based data access control, lineage tracking, and encryption for secure data workflows Automate infrastructure and data deployments using CDK, Terraform, or CloudFormation Drive data modelling standards (Star/Snowflake, 3NF, Data Vault) and ensure data quality and governance Collaborate with data scientists, DevOps, and business stakeholders to deliver end-to-end data solutions Mentor junior engineers and lead code reviews and architecture discussions Participate in client-facing activities including requirements gathering, technical proposal preparation, and solution demos Must-Have Qualifications: AWS Expertise: Proven hands-on experience with AWS Glue, Redshift, Athena, S3, Lake Formation, Kinesis, Lambda, Step Functions, EMR, and Cloud Watch PySpark & Big Data: Minimum 2 years of hands-on PySpark/Spark experience for large-scale data processing ETL/ELT Engineering: Expertise in Python, dbt, or similar automation frameworks Data Modelling: Proficiency in designing and implementing normalized and dimensional models Performance Optimization: Ability to tune Spark jobs with custom partitioning, broadcast joins, and memory management CI/CD & Automation: Experience with GitHub Actions, Code Pipeline, or similar tools Consulting & Pre-sales: Prior exposure to client-facing roles including proposal drafting and cost estimation Good-to-Have Skills: Knowledge of Iceberg, Hudi, or Delta Lake file formats Experience with Athena Federated Queries and AWS OpenSearch Familiarity with Data Zone, Data Brew , and data profiling tools Understanding of compliance frameworks like GDPR, HIPAA, SOC2 BI integration skills using Power BI, Quick Sight, or Tableau Knowledge of event-driven architectures (e.g., Kinesis, MSK, Lambda) Exposure to lake house or data mesh architectures Experience with Lucid chart, Miro , or other documentation/storyboarding tools Why Join Us? Work on cutting-edge AWS data platforms Collaborate with a high-performing team of engineers and architects Opportunity to lead key client engagements and shape large-scale solutions Flexible work environment and strong learning culture
