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Early Applicant
  • Posted 19 hours ago
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Job Description

About The Opportunity

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.

Skills & Qualifications

  • Must-Have
  • AWS Glue
  • Amazon S3
  • AWS Lambda
  • Amazon Redshift
  • Amazon Athena
  • Python
  • SQL
  • ETL/ELT
  • Preferred
  • AWS Step Functions
  • AWS MWAA
  • Apache Airflow

Benefits & Culture Highlights

  • 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.

Skills: glue,aws,etl,athena,sql,python,cloud,amazon redshift,aws lambda

More Info

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Key Skills

Amazon Athena

AWS Step Functions

ETL ELT

AWS MWAA

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