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Ameriprise Financial Services, LLC
Principal Lead- Product Data Engineer
Ameriprise Financial Services, LLC
Hyderabad•On-site•8-11 Yrs•2 days ago
Job description
Overview
Be part of an inclusive, collaborative culture that rewards you for your contributions, and work with other talented individuals who share your passion for doing great work.
Responsibilities
- The Technical Product Analyst (TPA) plays a pivotal role in an engineering driven delivery model. Unlike traditional Business Systems Analyst roles, this position requires strong technical depth and the ability to directly participate in solution design, data modeling, and implementation readiness.
- The role partners closely with Product Owners, Data Engineers, Solution Architects, and Platform Engineering teams to ensure clarity, technical feasibility, and executional excellence across initiatives involving cloud data platforms, analytics, and automation.
- Product & Requirement Translation
- Partner with Product Owners and stakeholders to translate business outcomes into technically actionable, build‑ready requirements
- Decompose epics and features into engineering‑backed user stories with clear acceptance criteria and technical context
- Ensure alignment between product intent, architectural standards, and platform capabilities
- Technical & Engineering Collaboration
- Act as a technical conduit between product and engineering teams, ensuring shared understanding of design trade‑offs and constraints
- Participate in solution discussions, architecture reviews, and technical refinement sessions
- Validate requirements against data models, APIs, pipelines, and cloud infrastructure patterns
- Hands‑On Technical Contribution
- Contribute directly to data analysis, SQL queries, schema definitions, metadata documentation, and pipeline validation
Qualifications
- Support engineering teams with implementation‑level artifacts such as data contracts, business logic mapping, and quality rules
- Validate delivered solutions through hands‑on testing, data reconciliation, and functional verification
- Data Quality, Reliability & Automation
- Define and embed data quality checks, reconciliation logic, and reliability metrics into delivery workflows
- Support automation of validation, monitoring, and reporting wherever feasible
- Partner with engineers to ensure observability, lineage, and governance considerations are addressed early
- Delivery & Operational Excellence
- Enable faster, more predictable delivery by reducing ambiguity and rework through high‑quality technical documentation
- Support backlog prioritization with a clear understanding of technical dependencies and delivery risks
- Contribute to continuous improvement of delivery processes and engineering best practices
- Technical Skills
- Strong hands‑on experience with SQL and data analysis across large datasets
- Solid understanding of cloud data platforms (AWS, Azure, or GCP)
- Familiarity With Modern Data Architectures
- Data lakes / Lakehouses
- ELT/ETL pipelines
- Streaming or batch data processing
- Working Knowledge Of
- APIs and data integration patterns
- Data modeling (conceptual, logical, and physical)
- Data quality and reconciliation frameworks (SODA)
- Comfortable working in Agile / DevOps delivery models
- Product & Analytical Skills
- Ability to connect business objectives to technical implementation details
- Strong analytical mindset with the ability to reason through complex data and system interactions
- Collaboration & Communication
- Proven ability to effectively collaborate with engineering‑heavy teams
- Clear, concise communicator capable of documenting complex technical concepts for diverse audiences
- Comfortable challenging assumptions and driving clarity in ambiguous problem spaces
- Exposure to automation, orchestration, or CI/CD pipelines