Staff Engineer Data [T500-23515]

About Albertsons Companies Inc. (ACI):

As a leading food and drug retailer in the United States, Albertsons Companies, Inc. operates over 2,200 stores across 35 states and the District of Columbia. Our well-known banners across the United States, including Albertsons, Safeway, Vons, Jewel-Osco and others, serve more than 36 million U.S customers each week.

We build and shape technology solutions that solve customers problems every day, making things easier for them when they shop with us online or in a store. We have made bold, strategic moves to migrate and modernize our core foundational capabilities, positioning ourselves as the first fully cloud-based grocery tech company in the industry.

Our success is built on a one-team approach, driven by the desire to understand and enhance the customer experience. By constantly pushing the boundaries of retail, we are transforming shopping into an experience that is easy, efficient, fun and engaging.

About Albertsons India Capability Center:

At Albertsons India Capability Center, we're not just pushing the boundaries of technology and retail innovation, we're cultivating a space where ideas flourish and careers thrive. Our workplace in India is a vital extension of the Albertsons Companies Inc. workforce and important to the next phase in the companys technology journey to support millions of customers lives every day.

At the Albertsons India Capability Center, we are raising the bar to grow across Technology & Engineering, AI, Digital and other company functions, and transform a 165-year-old American retailer. At Albertsons India Capability Center, associates collaborate directly with international teams, enhancing decision-making processes and organizational agility through exciting and pivotal projects. Your work will make history and help millions of lives each day come together around the joys of food and inspire their well-being.

Staff Data Engineer Data Governance:

About the Role:

As a Staff Data Engineer on the Data Governance team, you will define the technical strategy and architecture for data quality, metadata, lineage, and observability across the enterprise. You will solve the most complex data challenges, own platform-level decisions, and influence standards and engineering patterns across multiple domains. This role blends architecture, strategy, and hands-on engineering leadership.

Key Responsibilities:

• Define the long-term architecture for governance-aware pipelines, metadata flows, lineage, and data quality automation across GCP.
• Architect highly optimized, large-scale Big Query solutions and cross-platform governance integrations.
• Lead implementation of reusable Python frameworks for data validation, profiling, and metadata processing.
• Establish technical standards for SQL practices, schema modeling, pipeline patterns, and data contracts.
• Lead creation of Power BI governance dashboards that serve as authoritative reporting for DQ health, lineage coverage, ownership status, and compliance indicators.
• Drive adoption of enterprise governance tools (Alation, Monte Carlo) and integrate them with orchestrated pipelines.
• Partner with senior leadership to drive governance roadmap, privacy strategy, and compliance readiness.
• Lead deep investigations into high-impact data incidents; guide teams in prevention and architectural hardening.
• Mentor senior engineers and elevate engineering practices across domains.
• Ability to interpret architecture diagrams, even if not creating them

Required Skills:

• 8+ years of experience in data engineering, with proven architectural leadership.
• Mastery of Python for automation frameworks, data processing, and scalable code design.
• Mastery of SQL and advanced Big Query and GCP optimization (partitioning, clustering, cost optimization, query rewrites).
• Experience on API, JSON, XML files.
• Expert-level understanding of data stack (Big Query, Composer, GCS, IAM, DLP concepts, Snowflake, Azure, MongoDB, Cosmos DB).
• Extensive experience designing batch / ELT pipelines and governance-driven workflows.
• Deep experience in data quality strategy, rule frameworks, validation automation, and metadata-driven design.
• Strong communication and cross-domain leadership skills.
• Fluency with information models, industry standards, and agile architecture patterns.

Nice to Have

• Architecture leadership with Monte Carlo hybrid observability deployments.
• Experience scaling Alation metadata ingestion, CDE frameworks, and governance workflows.
• Advanced orchestration patterns with Airflow / Cloud Composer.
• Working knowledge of CCPA, data retention, access patterns, and protection frameworks.
• Understanding of AI technologies, RAGs, MLOPS.