Job Purpose and Impact
The Senior Data Engineer designs, builds, and operates scalable, reliable data products and platforms that power analytics, reporting, and downstream applications. This role owns end‑to‑end delivery of batch and streaming data pipelines on a contemporary AWS‑based cloud data platform, applying robust engineering patterns to ensure performance, security, observability, and cost efficiency.

With minimal supervision, the role partners closely with product, analytics, and platform teams to translate business requirements into robust technical solutions across a Lakehouse (Iceberg) and approved warehousing platforms (e.g., Snowflake). The Senior Data Engineer also mentors other engineers, drives code quality, and raises the engineering bar across the organization.

Key Accountabilities
Data & Analytical Solutions
Designs and delivers scalable data products using standard cloud and data engineering architectures.
Owns technical decisions (batch vs. streaming, Lakehouse vs. warehouse) and ensures solutions meet reliability, security, governance, latency,



and cost requirements.
Reviews designs and contributes reusable components, templates, and standards.

Data Pipelines
Builds and operates end‑to‑end batch and streaming pipelines.
Implements transformations using SQL/dbt and PySpark as needed.
Integrates real‑time or event‑driven ingestion using Kafka.
Orchestrates workflows with Airflow; establishes SLAs/SLOs and CI/CD‑based deployments.

Data Systems & Architecture
Optimizes data architectures for performance, scalability, and cost.
Applies best practices for Iceberg table design, incremental processing, and query optimization across Hive, Impala, Snowflake, and RDBMS.
Diagnoses systemic issues and drives remediation with platform teams.

Data Infrastructure (AWS)
Leads technical readiness across dev/test/prod settings.
Works hands‑on with AWS services including S3, Glue, Lambda, IAM, and SageMaker.
Partners with gove

📌 Senior Data Engineer Bengaluru
🏢 Cargill
📍 Bengaluru