Jobs → Data & Analytics → Data / AI Native Engineer

About the Role We are seeking a Data / AI Native Engineer to join our team. This role involves designing, building, and optimizing enterprise-scale data pipelines using Databricks and AWS Lakehouse technologies. Key Responsibilities • Design, build, optimize, and support enterprise-scale Databricks and AWS Lakehouse data pipelines using Spark and PySpark • Develop Databricks solutions leveraging Delta Lake, Medallion Architecture (Bronze/Silver/Gold), and Unity Catalog • Develop high-volume batch and streaming pipelines using PySpark, ensuring scalability, performance, reliability, data quality, and maintainability • Design and implement modern lakehouse engineering patterns including SCD Type 2, Change Data Capture (CDC), idempotent writes, schema evolution, and data contracts • Work across the AWS data ecosystem, including technologies such as S3, Glue, Lambda, EMR, Redshift, Kinesis, and related AWS services • Use GitHub Copilot and/or Claude Code CLI as part of the daily engineering workflow • Rapidly develop proofs of concept and MVPs using AI-assisted development • Apply AI capabilities directly within the data-engineering lifecycle • Build data foundations for AI-enabled products • Design and develop high-volume streaming pipelines using technologies such as Spark Structured Streaming, Kafka, Kinesis, and Databricks Auto Loader • Develop and orchestrate enterprise data pipelines using technologies such as Databricks Workflows, Delta Live Tables, Airflow, and dbt • Implement secure and governed data-engineering practices using Unity Catalog • Lead technically complex data-engineering initiatives • Partner with architects, software engineers, product owners, source-system teams, governance teams, analytics teams, AI teams, and business stakeholders • Remain actively hands-on with PySpark, Databricks, AWS, and software-engineering activities Requirements • 13+ years of experience in IT • Strong experience with Databricks, AWS Lakehouse, Spark, and PySpark • Experience with Delta Lake, Medallion Architecture, and Unity Catalog • Knowledge of AWS data ecosystem technologies • Familiarity with AI-assisted development tools • Experience with streaming pipelines and data orchestration tools • Understanding of secure and governed data-engineering practices • Ability to lead technically complex initiatives • Strong collaboration and communication skills