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💼 Full-time🗓 2026-07-26

Core

Build and scale serverless, AWS-native data infrastructure to deliver a unified marketing data model serving GenAI initiatives, measurement scientists, and marketing analysts.

Role type

Senior Data Engineer (Marketing Analytics & Platform)

Builds

Unified marketing data model, automated ETL/ELT pipelines, Gold data sets, data lake tables, and API-first data delivery patterns.

Domain

Marketing analytics, Data Engineering, Cloud Infrastructure (AWS)

Deliverable

production ML models | product features | dashboards & analysis | infrastructure

Required skills

Data modeling, Warehousing, ETL/ELT pipeline development, SQL, Python, Spark, AWS services (Redshift, S3, Glue, Lambda, Step Functions), Data quality frameworks, Data security, Metadata management.

Preferred skills

None stated

Technologies

AWS (Redshift, S3, Glue, Lambda, SageMaker, Step Functions, SNS, CloudWatch), Python, Spark, SQL

Responsibilities

Develop and maintain automated ETL/ELT pipelines with monitoring; Build and optimize Gold data sets and fact/dimension tables; Develop and optimize Redshift and data lake tables for performance; Build and maintain data quality frameworks; Develop and maintain data security and access controls; Maintain data catalogs and lineage documentation; Partner with scientists and analysts to deliver data solutions.

Seniority

Mid-level (2+ years experience)

Rewrite
## About the role 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
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