Data Engineer

Overview

We're looking for a Data Engineer to build and scale the next-generation data infrastructure. You'll work with a serverless, AWS-native stack i.e. Redshift, S3, Glue, Lambda, SageMaker, Step Functions, SNS, CloudWatch, and more - to deliver the unified marketing data model that serves new GenAI initiatives, measurement scientists, marketing analysts, and downstream APIs.

You'll join a tight, high-impact team solving problems at the intersection of marketing analytics, data science enablement, and platform engineering. You'll experience a culture that values ownership, cross-functional collaboration, and data-driven decision making.

Qualifications
• 2+ years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Bachelor's degree in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline

Key job responsibilities
• Develop and maintain automated ETL/ELT pipelines (with monitoring and alerting) using Python, Spark, SQL, and AWS services (S3, Glue, Lambda, Step Functions, SNS, SQS, CloudWatch).
• Build and optimize the Gold data sets in the marketing data model - designing fact and dimension tables that unify customer journey, web analytics, campaign, revenue, and attribution data at enterprise scale.
• Develop and optimize Redshift and data lake tables using best practices for DDL, physical/logical modeling, data partitioning, compression, and query performance tuning.
• Build and maintain data quality frameworks, including validation, reconciliation, and anomaly detection, to ensure trusted, reliable data for downstream science and analytics consumers.
• Develop and maintain data security, access controls, encryption, and permissions for enterprise-scale data-warehouse and data-lake implementations.
• Maintain data catalogs, metadata, lineage documentation, and self-service tooling for internal marketing and science consumers.
• Partner with measurement scientists, marketing analysts, and cross-functional engineering teams to gather requirements and deliver data solutions that directly inform marketing investment strategy.
• Contribute to API-first data delivery patterns, enabling science-as-a-service consumption of marketing data assets.

*Note - * Immediate Joiners

No of Positions - 8