Senior Technical Lead

Technology, Data & Digital · Data, AI & Analytics · Data Engineering · Data Science · Software Engineering

In short

We are seeking a Senior Analytics Engineer with 7-10 years of experience to design and build scalable data lakehouse architectures on AWS. This role involves developing ETL/ELT pipelines, implementing data governance, and supporting ML feature engineering using AWS services like Glue, Athena, Lake Formation, and SageMaker.

Responsibilities

Design and build scalable data lakehouse architectures on AWS using Apache Iceberg.
Develop and optimize analytics query layers using Amazon Athena.
Implement fine-grained data access, governance, and permissions using AWS Lake Formation.
Build and maintain ETL/ELT pipelines using AWS Glue.
Support ML feature engineering and model-ready data pipelines using Amazon SageMaker.
Own analytics/dimensional data modelling (star/snowflake schemas, fact & dimension design).
Apply DBT for transformation workflows, testing, and documentation.
Partner with data engineers, data scientists, BI teams, and client stakeholders.
Ensure data quality, lineage, and governance standards.
Contribute to architecture decisions, code reviews, and best practices.

Requirements

Strong hands-on experience with AWS analytics services: Glue, Athena, Lake Formation, S3.
Practical experience with Apache Iceberg (or similar open table formats like Delta Lake/Hudi).
Experience with Amazon SageMaker for supporting ML/analytics workflows.
Solid grounding in analytics/dimensional data modelling (star schema, snowflake schema, slowly changing dimensions, semantic modelling).
Strong SQL skills and experience optimizing queries on large-scale distributed data.
Experience with Python and/or PySpark for data transformation and pipeline development.
Understanding of data governance, cataloging, and access control concepts on AWS.

Desired Qualifications

Hands-on experience with DBT (data build tool) for transformation, testing, and documentation.
Exposure to CI/CD for data pipelines and infrastructure-as-code (Terraform/CloudFormation).
Familiarity with BI tools such as QuickSight, Tableau, or Power BI.
AWS certifications (Data Analytics Specialty, Machine Learning Specialty).

Benefits

Supercharge your potential.
Find your career.
Find your spark.
A place that knows that helping its customers stay on top starts by putting its people first.

Skills

AWS GlueAmazon AthenaAWS Lake FormationAmazon S3Apache IcebergDelta LakeHudiAmazon SageMakerSQLPythonPySparkDBTTerraformCloudFormationQuickSightTableauPower BI

#Analytics Engineer#AWS#Data Lakehouse#Apache Iceberg#Amazon Athena#AWS Lake Formation#AWS Glue#Amazon SageMaker#ETL#ELT#Data Modelling#DBT#SQL#Python#PySpark#Data Governance

About HCLTech

Supercharging progress through technology and innovation

HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered around digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2022 totaled $12.1 billion. To learn how we can supercharge progress for…

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