Sr. Data Engineer – (Customer Data Platform)

Role: Sr. Data Engineer (Customer Data Platform)

Location: Atlanta, GA or Frisco, TX

Experience: FAANG/product Tier 1 company experience is mandatory.

Mandatory Skills: Python, Databricks, PySpark, Delta Lake, Snowflake, SQL

About the Role

Sr Engineer, Data designs and delivers scalable data architectures and advanced data engineering solutions across on-premises, cloud, and hybrid platforms to support enterprise analytics and customer intelligence use cases.

This role partners closely with data engineers, architects, and analytics teams to analyze, design, and optimize data warehouse and analytics solutions that power personalization and data-driven decision-making within the customer data platform.

The Sr Engineer provides hands-on technical leadership, mentors engineers, and drives the evolution of modern data architectures.

Success is measured by solution effectiveness, scalability, performance, and growth in team capability and architectural maturity.

What You ll Do

Design and develop advanced data engineering solutions that enable data pipelines, visualization, and analytical tools Architect and implement scalable data platforms across on-premises, cloud, and hybrid environments

Build, optimize, and operate complex batch and real-time and near real-time streaming data pipelines

Build, optimize, and operate low-latency, sub-second APIs on highly scalable, fault-tolerant architectures.

Design and maintain high-throughput data pipelines to support agentic AI workloads and real-time multi-agent MCP orchestration.

Build and maintain enterprise-scale Graph Databases that power organizational knowledge graphs and connected data experiences. Perform data wrangling, exploration, and discovery across heterogeneous data sources to generate insights

Lead development of large-scale data processing solutions using Databricks and Spark technologies

Design and optimize relational, NoSQL, and analytical data models

Contribute to team knowledge sharing and advancement of data engineering standards and capabilities

Mentor engineers to strengthen technical skills, delivery quality, and professional growth

Support project definition activities including estimation, planning, and scoping in partnership with management

What You ll Bring

Bachelor s Degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience

8+ years of hands-on experience designing, building, and supporting data engineering solutions

Strong experience developing and migrating data solutions across cloud platforms Demonstrated technical leadership and mentoring experience

Strong analytical and problem-solving skills applied to complex data challenges Ability to manage multiple concurrent initiatives with strong organizational and prioritization skills

Passion for learning and applying new data and platform technologies

Must Have Skills

Core Data Engineering & Platforms

Advanced experience designing and building complex data pipelines using Python and SQL

Strong experience with cloud platforms and services, including: Azure (Data Factory, Data Lake, Event Hub, Functions, Web Apps, Cosmos DB) Databricks with PySpark, Spark SQL, and Scala Spark, including cluster configuration, autoscaling, and performance optimization (e.g., Photon) Snowflake data warehousing, including schema design (star/snowflake), query optimization, and cost/performance tuning

Expertise in SQL, NoSQL, and relational database design and development APIs, Streaming & Integration

Proficiency designing and consuming RESTful APIs with secure authentication and authorization (OAuth 2.0, JWT, API keys)

Experience using Postman and Swagger/OpenAPI for API testing, documentation, and validation

Working knowledge of message queuing, stream processing, and highly scalable big-data data stores

Engineering Practices Advanced knowledge of data pipeline development using Python and experience with languages such as SQL, DAX, Java, Scala, and/or Go Experience performing root-cause analysis and using technology to solve complex business problems

Experience adopting AI-assisted development tools and building AI-powered agents or agentic workflows to automate engineering