Sr. Data Engineer

Masco Corporation•Indianapolis, IN

1d•$88,700 - $139,260

About The Position

Delta Faucet Company is seeking a Senior Data Engineer to lead the design, development, and scaling of enterprise data pipelines that power omni-retail analytics, advanced modeling, and AI/ML initiatives. This role is responsible for managing a complex POS-driven data ecosystem spanning multiple retailers, APIs, third-party data providers, and internal enterprise systems. The ideal candidate will bring strong technical expertise and a strategic mindset to transform fragmented data workflows into a scalable, governed, and high-performing data platform. This role plays a critical part in modernizing the organization’s data architecture by enabling consistent, reliable, and feature-ready datasets that support statistical modeling, AI use cases, and executive decision-making. The Senior Data Engineer will work closely with analytics, data science, and business stakeholders to standardize data definitions, improve data quality, and reduce reliance on manual data preparation processes.

Requirements

5+ years of experience in data engineering, data platform development, or related roles
Proven experience designing and maintaining scalable data pipelines in a cloud-based environment
Strong proficiency in SQL and Python for data transformation and pipeline development
Hands-on experience with distributed data processing frameworks (e.g., PySpark, Spark)
Experience working with APIs and integrating structured and unstructured data sources
Strong understanding of data modeling concepts (e.g., dimensional modeling, fact/dimension design)
Experience implementing data quality, validation, and monitoring solutions
Ability to work across technical and business teams to deliver data-driven solutions
Strong problem-solving skills with the ability to manage complex data environments

Nice To Haves

Experience working with Databricks, lakehouse architectures, or similar platforms
Exposure to AI/ML workflows, including feature engineering and model data preparation
Familiarity with POS and retail data ecosystems (e.g., Home Depot, Lowe’s, Walmart, Amazon)
Experience with third-party syndicated data sources (e.g., Stackline, Datavations, SimilarWeb)
Knowledge of orchestration tools (e.g., Airflow, Azure Data Factory)
Experience with cloud platforms (Azure, AWS, or GCP)
Background in analytics engineering or building semantic/curated data layers

Responsibilities

Design, build, and maintain scalable data pipelines integrating POS, eCommerce, third-party, and enterprise data sources
Lead cross-platform data integration across APIs, file ingestion, cloud storage, and analytics environments
Develop and manage end-to-end data workflows from ingestion through transformation to consumption
Create and maintain feature-ready datasets to support statistical modeling, machine learning, and AI initiatives
Standardize data models, schemas, and transformation logic across retailers and product hierarchies
Implement automated data quality checks, validation frameworks, and monitoring processes
Optimize data pipelines for performance, scalability, and cost efficiency
Reduce manual data processing by automating ingestion and transformation workflows
Collaborate with analytics and data science teams to translate business requirements into scalable data solutions
Establish and enforce best practices for data governance, consistency, and documentation
Support integration of enterprise systems such as SAP, Salesforce, and Snowflake into the analytics ecosystem
Mentor and guide team members on data engineering best practices and scalable design patterns