Overview

Line of Service Advisory

Responsibilities

• We are looking for an experienced AWS Data Engineer with 4–8 years of hands-on experience in designing, developing, and maintaining scalable data pipelines and cloud-based data platforms.
• The ideal candidate will have strong expertise in AWS, Snowflake, Apache Airflow, Python, PySpark, and SQL, with a solid understanding of data warehousing, ETL/ELT, data modeling, and performance optimization.
• The candidate will work closely with data architects, analysts, application teams, and business stakeholders to build reliable and scalable data solutions.
• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using AWS services.
• Build and orchestrate data pipelines using Apache Airflow, including DAG development, scheduling, monitoring, retries, dependencies, and error handling.
• Develop data processing and transformation solutions using Python and PySpark.
• Design and implement data warehouse solutions using Snowflake.
• Develop complex SQL queries, stored procedures, views, CTEs, and data transformations.
• Work with AWS services such as S3, Glue, Lambda, EMR, Athena, Redshift, and IAM.
• Build batch and, where required, near-real-time data ingestion pipelines.
• Implement data ingestion from APIs, databases, files, and other source systems into AWS/Snowflake.
• Implement Snowflake features such as Snowpipe, Streams, Tasks, stages, file formats, and secure data sharing.
• Develop scalable Spark/PySpark jobs and optimize transformations, joins, partitioning, caching, and resource utilization.
• Implement data quality checks, validation, reconciliation, and monitoring mechanisms.
• Collaborate with cross-functional teams in an Agile/Scrum environment.
• Create technical documentation for data pipelines, workflows, data models, and operational procedures.

Qualifications

• Good understanding of data warehousing and dimensional data modeling.
• Good understanding of Git and CI/CD.
• AWS Services
• S3, Glue, Lambda, EMR, Athena, Redshift, IAM
• Data Warehouse
• Programming
• PySpark, Apache Spark
• Orchestration
• Apache Airflow
• SQL, Relational Databases
• Data Engineering
• ETL/ELT, Data Pipelines, Data Integration
• Data Modeling
• Star Schema, Snowflake Schema, Dimensional Modeling
• Kafka, dbt, Terraform, Databricks
• Knowledge of Lakehouse / Medallion Architecture.
• Snowflake certification such as SnowPro Core.
• Exposure to Docker/Kubernetes is a plus.
• Years of experience required:
• Data Engineering
• Optional Skills
• Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline {+ 38 more}
• Desired Languages (If blank, desired languages not specified)
• Travel Requirements
• Available for Work Visa Sponsorship?
• Government Clearance Required?
• Job Posting End Date
• May 11, 2026

Education

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
• Preferred Skill sets:
• AWS Lambda, EMR, Athena, Redshift, Kinesis, Step Functions, IAM.
• Snowflake Snowpipe, Streams, Tasks, Dynamic Tables, Time Travel and performance tuning.
• B.Tech/MCA/BCA/M.tech
• Degrees/Field of Study required: Master of Engineering, Bachelor of Engineering
• Degrees/Field of Study preferred:
• Certifications (if blank, certifications not specified)