Sr. Tech Lead - AWS

We are looking forward to hire AWS Professionals in the following areas :

Role Overview

We are looking for a AWS Senior Tech lead with strong knowledge on AWS Data Lake Architecture and is responsible for designing, building, and enhancing the organization s enterprise data lake environment. This role oversees data ingestion from multiple source systems, ETL design, data quality frameworks, metadata management, and integration pipelines feeding downstream platforms, including Anaplan. The architect will drive end-to-end data lake architecture, ensure scalability, and guide ongoing developments and future roadmap initiatives.

Key Responsibilities

• Design and architect an enterprise-grade AWS Data Lake using S3, Glue, Airflow, Lake Formation, RED Shift, Lambda, Athena, and related services.
• Build and enhance ingestion pipelines for multiple source systems / Unstructured data sources.
• Design and optimize ETL/ELT frameworks (Glue, Spark, etc. ) used to transform and prepare data for consumers.
• Own data lake data models, folder structures, partitioning strategies, and schema evolution processes.
• Implement data governance, data cataloging, access control, and lineage using Lake Formation and Glue Catalog.
• Improve and optimize performance of ETL jobs, Spark workloads, queries, and storage layers.
• Establish data quality, validation, and reconciliation frameworks across source systems and transformed layers.
• Automation and management of data load queues and pipeline management.
• Work closely with downstream consumers to ensure reliable feeds and consistent data definitions.
• Lead technical direction for new data lake developments, feature enhancements, and integration of new data sources.
• Create and maintain architecture diagrams, technical documents, data flow maps, and ETL logic documentation.
• Ensure adherence to cloud best practices, security standards, and cost optimization guidelines.

Required Skills & Qualifications

• 10+ years of experience in AWS data engineering or data architecture, with proven data lake ownership.
• Strong expertise in AWS services: S3, Glue, Lake Formation, IAM, Lambda, Athena, EMR/Spark, Step Functions, KMS, Airflow, RedShift.
• Deep experience building scalable ETL/ELT pipelines using Glue, Spark, or Lambda.
• Strong understanding of data lake architecture, file formats, partitioning, schema evolution, and metadata management.
• Experience with multi-source data ingestion (APIs, databases, flat files, streaming).
• Strong knowledge of data modelling, data quality frameworks, and governance practices.
• Hands-on experience integrating data with downstream systems such as Anaplan, data warehouses, or BI tools.

Preferred Qualifications

• Experience with Redshift, DynamoDB, or streaming platforms (Kinesis/MSK).
• Familiarity with Terraform or CloudFormation for IaC.
• Background supporting Finance or FP&A use cases is an advantage.
• Experience in building data lineage, monitoring, and observability frameworks.
• Knowledge of SQL, Python, and distributed computing concepts.

Certifications to be added

Our Hyperlearning workplace is grounded upon four principles

• Flexible work arrangements, Free spirit, and emotional positivity
• Agile self-determination, trust, transparency, and open collaboration
• All Support needed for the realization of business goals,
• Stable employment with a great atmosphere and ethical corporate culture