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Job Title
Senior Technical Lead – AWS Data Engineering
Location
PAN India
Life Sciences & Healthcare / Technology Provider
Introduction to the Organization
HCLTech is a global leader in technology solutions, committed to driving innovation and excellence across diverse industries. With a presence in over 50 countries and a workforce of more than 220,000 professionals, HCLTech empowers organizations to transform digitally through cutting-edge products, services, and platforms. Renowned for its customer-centric approach, industry expertise, and dedication to sustainability, HCLTech has been recognized for delivering impactful solutions that accelerate business growth and foster a culture of collaboration and continuous learning.
Overview of the Role
The Senior Technical Lead – AWS Data Engineering will serve a critical function within HCLTech's Life Sciences and Healthcare division. This role is responsible for architecting and leading the development of advanced data solutions leveraging AWS cloud technologies. The position directly influences business-critical pharmaceutical analytics, compliance, and innovation, ensuring the delivery of scalable, secure, and efficient data workflows that support regulatory and operational excellence.
Detailed Responsibilities
Skill Requirements
Job ID: 151396055
Skills:
Apache Flink, Pyspark, Apache Spark, Kafka, Sql, Terraform, Gitlab, Python, Aws S3, Apache Iceberg, Airflow, PeerDB, ClickHouse, Debezium, GitHub Actions, Temporal, Delta Lake, Trino, Apache Hudi
Skills:
amazon dynamodb , Data Modeling, Amazon Redshift, Etl Development, AWS Glue, Data Warehousing, Sql, AWS Data Catalog Crawler, Data Pipelines, Data Due Diligence
Skills:
Sql, Databricks, S3, Emr, Lambda, Pyspark, AWS, Kubernetes, Iam, Docker, Git, Redshift, Airflow, Glue
Skills:
Pyspark, AWS Glue, Apache Spark, Sql, Git, Amazon Redshift, Python, Apache Iceberg, Parquet, Amazon Athena, AWS DMS, AWS Lake Formation, AWS DataZone, Data Lake and Lakehouse architectures, CI CD pipelines, AWS Kinesis
Skills:
Spark, Sql, Data Modeling, Python, Performance Tuning, Git, partitioning strategies, microservices-based architectures