We are seeking an experienced Data Engineer to join the Enterprise Data and Analytics team. This is a hands-on, execution-focused role responsible for building enterprise-grade data platforms and delivering reliable, scalable end-to-end data pipelines. The role focuses on ingesting, processing, and hydrating data into the enterprise Data Lake to support analytics, reporting, and downstream applications.

You will work closely with business analysts, product teams, and platform engineers to translate business requirements into scalable data solutions while applying engineering best practices and DevOps principles to ensure quality, reliability, and maintainability across cloud-based data environments.

Key Responsibilities

Build and maintain robust data ingestion pipelines integrating flat files, APIs, relational databases, and third-party platforms.

Develop ETL and ELT workflows to support efficient and reliable data movement into the enterprise Data Lake.

Implement data processing and data hydration across Data Lake layers including Staging, Raw, Conformed, and Curated with a strong emphasis on data quality and consistency.

Work extensively with cloud services for data ingestion, storage, access control, and data lifecycle management.

Configure, monitor, and troubleshoot enterprise data pipelines using orchestration and workload scheduling tools.

Develop reusable data views, interfaces, and APIs to support efficient data consumption.

Implement DevOps best practices including CI/CD pipelines, version control, automated deployments, and environment management.

Participate in code reviews, contribute to engineering standards, and ensure production-ready data solutions.

Collaborate with cross-functional teams to deliver scalable, high-quality data engineering solutions using Agile methodologies.

Required Skills

PL/SQL.

Snowflake.

Python.