About the Chance
A dynamic talent solutions firm operating at the intersection of cloud infrastructure and data engineering, we partner with enterprises to build scalable, secure, and high-performance data platforms on AWS. Our engineers architect, deploy, and optimize data pipelines, lakes, and warehousing solutions that power real-time analytics, machine learning, and business intelligence across industries.
Role & Responsibilities
- Design and implement scalable ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions for batch and real-time data ingestion.
- Build and maintain data lakes on S3 with proper partitioning, cataloging (Glue Data Catalog), and governance using IAM and Lake Formation.
- Orchestrate data workflows via AWS MWAA or Step Functions, monitor pipeline health, and ensure SLA compliance.
- Optimize Redshift or Snowflake (if integrated) for performance and cost using materialized views, distribution keys,
and query tuning.
- Implement data quality checks, lineage tracking, and alerting using CloudWatch, Athena, and custom Python scripts.
- Collaborate with analytics and ML teams to deliver clean, curated datasets for dashboards and model training.
- Onsite collaborative environment with access to cloud certification sponsorships.
- Direct exposure to enterprise-scale AWS data architectures and cross-functional teams.
- Fast-paced, learning-driven culture with growth acceleration for high performers.