We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and the underlying database infrastructure that supports analytics and reporting across the organization. This role sits within the Data Integration and Architecture team and is central to the ongoing data lake buildout.
This role will focus on ensuring database stability, proper indexation, reliable backups, performant pipelines, and sound data model and schema design. Strong collaboration with the analytics team will be essential to ensure they have a reliable, well-governed platform to build on.
Responsibilities to Include
Database Infrastructure & Reliability
Build, optimize, and maintain data models and schemas within PostgreSQL, ensuring proper indexation, partitioning, and structural integrity to support downstream consumption.
Own database backup, recovery, and disaster recovery procedures to ensure data durability and business continuity.
Monitor database health, query performance, and resource utilization, proactively addressing issues before they impact downstream systems.
Contribute to the architecture and continued buildout of the organization's data lake on Azure, including storage design, lifecycle policies, and environment reliability.
Take ownership of deployment, security, and environment configuration from vendor teams, partnering with infrastructure and DevOps resources to bring these capabilities in-house.
Data Pipelines & Integration
Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory to ingest, transform, and load data from a variety of source systems.
Implement and enforce data quality checks, monitoring, and alerting across pipelines.
Troubleshoot pipeline failures and performance bottlenecks, performing root cause analysis and implementing lasting fixes.
Governance & Collaboration
Partner with business stakeholders and the analytics team to understand data ingestion requirements, ensuring data models and schemas are designed to meet current and future needs without duplicating tables or data across the environment.
Drive standardization and templatization of data structures, pipeline patterns, and ingestion processes to ensure consistency, reduce technical debt, and make the platform easier to scale.
Ensure the analytics team has access to clean, performant, and well-documented data by maintaining reliable data structures and pipeline outputs.
Document data flows, lineage, and pipeline logic to support governance and knowledge sharing.
What You Will Need
5+ years of experience in a data engineering role or a closely related function.
Strong proficiency with Azure Data Factory, including pipeline orchestration, linked services, and integration runtimes.
Solid SQL skills with hands-on experience managing PostgreSQL databases, including indexing strategies, partitioning, query optimization, backup and recovery, and performance tuning.
Familiarity with Azure data services such as Azure Data Lake Storage, Azure Containers, or Synapse Analytics.
Experience with Python or another scripting language for data transformation and automation tasks.
Experience administrating Azure environments, including resource management, access controls, and service configuration.
Understanding of data modeling concepts (star schema, Medallion structure, normalization/denormalization).
Comfort working with version control and implementing CI/CD practices for data pipeline deployment.
Strong communication skills and the ability to translate technical concepts for non-technical stakeholders.
Nice to Have
Experience with database monitoring tools, automated alerting, and infrastructure-as-code practices for data environments.
Exposure to EDI data flows or ERP systems such as NetSuite.
Background working in a consumer products, retail, or e-commerce environment.