Senior Data Engineer

What were looking for We are seeking a Senior Data Engineer with strong experience in building modern, scalable data platforms. You will work closely with customers, product teams, and engineering stakeholders to design and implement enterprise-grade data analytics solutions. This role requires deep expertise in data engineering, data modeling, and lakehouse architectures, along with the ability to lead technical discussions, mentor engineers, and drive best practices. What you ll do Build enterprise-grade data analytics platforms from scratch. Partner with customers on their product vision, roadmap and goals and design the high/low level technical designs. Build modern data analytics platforms using Apache Iceberg v2/v3, Data lakehouse or Medallion architecture, AWS Sagemaker Studio/Microsoft Fabric/Databricks, Python, Spark, AWS Glue, Kafka, Debezium. Design and Implement meta-data driven multi-source data integration pipelines for relational and non-relational databases, file systems to process GBs of data. Implement PHI-compliant data processing with automated data anonymization and PHI data stripping. Implement data quality frameworks and validation pipelines to grade data quality. Data modelling, and database design to ensure sub-minute query performance. Collaborate with tech experts, share learnings, do research and POCs to build reusable solutions. Mentor peer engineers, lead code reviews, conduct architecture discussions, publish Architecture Design Review Documents. drive technical excellence. Lead research, POCs, and prototypes to build reusable solutions and cool products in different domains like healthcare, media, IoT, e-commerce, mobile, networking, and lots more. To be successful in this role, you should have Qualification: BE/BTech in Computer Science from a recognized university. Experience: 6 to 8 years of hands-on experience in building data platforms and data engineering solutions Skills Strong proficiency in Python and PySpark for large-scale data processing Strong expertise in data modeling and schema design, including: Star and Snowflake schemas Normalized schemas (1NF, 2NF, 3NF) Slowly Changing Dimensions (SCD Type 1/2/3) Data Vault (Hubs, Links, Satellites) Denormalized/Wide-table patterns Strong SQL skills with experience in relational databases (PostgreSQL preferred). Proficient in analytical functions and joins (self, natural, left, right, inner, and outer joins), as well as window functions such as PARTITION BY, RANK, and related analytical operations. Partition data by date/key, use columnar formats (Parquet/Iceberg), implement incremental processing with checkpoints, optimize Spark with broadcast joins and proper executor sizing, leverage data skipping with Z-ordering, and process in parallel with distributed compute (Spark/Glue/EMR). Experience with AWS cloud services (S3, Glue, Athena, EMR, EC2, Sagemaker) Experience working in fast-paced Agile environment, with strong attention to detail and commitment to quality Hands-on experience with AWS Sagemaker Studio or Microsoft Fabric or Databricks platform on areas of Workspace, Clusters, SQL, Workflows, Catalog, Monitoring Hands-on experience in Apache Iceberg or similar lakehouse technologies Deep expertise in data warehouse and lakehouse architectures (Medallion, others) using Databricks, and Open-source stack Knowledge of data quality frameworks and validation techniques Must-Have Skills Strong experience with Data Lakehouse/Medallion architectures Hands-on data engineering experience using AWS SageMaker Studio or (Microsoft Fabric/ Databricks) AWS Glue, EMR, Athena, and S3 Expertise in Apache Iceberg (v2/v3) Strong programming skills in Python, Apache Spark, and SQL Good-to-Have Skills Experience with Debezium (CDC) and Apache Kafka Ability to lead data modeling and schema design initiatives Experience authoring Architecture Design Review (ADR) documents What you ll find here A culture of innovation: We only take up projects that challenge us to innovate. Our customers come to us for our technology expertise. Endless learning opportunities: Continuous learning is baked into our DNA. You ll always have the chance to learn new things and stay on top of the latest trends. Talented peers: Work alongside engineers from IITs, NITs, BITS, and other premier institutions. Work-life balance: We value work-life balance and offer flexible schedules, including remote work options, so you can thrive both professionally and personally. A great culture: Our employees love working here! 82% recommend Talentica to their friends, according to Glassdoor. Join us, and you ll see why! Recognition rewards: We don t just work hard, we celebrate success. Your contributions won t go unnoticed. We ll make sure youre recognized for the amazing work you do.