Senior Data Engineer
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Job Location:
Atlanta, GA - USA
Monthly Salary:
Not Disclosed
Posted on:
2 days ago
Vacancies:
1 Vacancy
Job Summary
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation information technology and services
Position: Senior Data Engineer
Location: Atlanta GA / Frisco TX / BellevueWA
Duration: 9 months
Job Type: Temporary Assignment
Work Type: Hybrid
Job Description
Job Overview
- We are seeking a Senior Data Engineer to lead the design and development of the scalable high-performance data architecture that underpins our Customer Data Platform (CDP) - the authoritative source of truth for customer data across the entire US adult population.
- This role owns the data foundations that make CDP trustworthy: robust pipelines rigorous quality frameworks and production-grade data architectures that deliver accurate timely customer profiles at massive scale.
- You will ensure that every downstream consumer - from personalization engines to AI/ML models to business intelligence - can rely on CDP data without hesitation.
- You will architect systems that handle billions of records across hundreds of source systems while maintaining the data quality governance and operational excellence that an authoritative platform demands.
Job Responsibilities
- Architect and develop scalable resilient batch and streaming data pipelines using ADF Databricks and Spark - designed for the throughput and reliability CDP demands at population scale
- Design and implement end-to-end data architecture across ADLS Snowflake Cosmos DB and SQL Server ensuring optimal storage strategies for different customer data workloads
- Define and enforce data modeling standards data contracts and schema evolution strategies that protect the integrity of CDP as the single source of truth
- Build and maintain data quality reconciliation and observability frameworks - ensuring every customer profile meets the accuracy and completeness thresholds required for trusted authoritative data
- Optimize performance scalability and cost efficiency of large-scale distributed data systems processing billions of customer records
- Develop and manage data ingestion frameworks for APIs event streams (Event Hub/Kafka) and enterprise systems - ensuring no customer touchpoint is missed
- Enable downstream AI/ML and GenAI use cases by preparing curated datasets feature-ready data and metadata layers that accelerate identity resolution and personalization
- Support RAG and search-based use cases by building reliable data pipelines for document ingestion indexing and retrieval (in collaboration with AI/ML teams)
- Implement and standardize CI/CD pipelines orchestration (Control-M) and DevOps practices for data workflows with production-grade reliability
- Drive improvements in data governance lineage and access patterns - ensuring CDP data is not only accurate but also secure and compliant
- Lead design reviews code reviews and technical mentoring for junior engineers raising the bar for engineering quality across the team
- Partner with cross-functional teams to align data platform capabilities with business needs ensuring CDP delivers the contextual experiences that drive company growth
- Troubleshoot complex production issues and implement long-term scalable fixes that strengthen platform resilience
Education and Work Experience
- Bachelors or Masters degree in Computer Science Engineering or related field
- 6 years of experience in data engineering and distributed data systems
- Proven experience designing and implementing enterprise-scale data platforms serving high-volume high-reliability use cases
- Strong experience in cloud-native architectures (Azure preferred)
Technical Skills
- Advanced programming: Python Spark (PySpark/Scala) SQL
- Azure ecosystem: ADF ADLS Databricks
- Data platforms: Snowflake Cosmos DB SQL Server
- Strong expertise in ETL/ELT design streaming architectures and data modeling for customer-centric data domains
- Experience with API integrations and event-driven architectures at scale
- Hands-on experience with data quality frameworks reconciliation techniques and monitoring - with a focus on trust and accuracy
- Familiarity with data support for AI/ML use cases (e.g. feature pipelines data preparation metadata management for identity resolution)
- Basic understanding of RAG vector search and LLM-driven applications (supporting role not primary ownership)
- Experience implementing data governance lineage and access controls in regulated environments
- Expertise in performance tuning and cost optimization for population-scale data processing
Knowledge Skills and Abilities
- Strong system design and architectural thinking for data platforms that must be both authoritative and performant
- Ability to handle large-scale complex data ecosystems spanning hundreds of source systems
- Leadership in driving engineering best practices data quality standards and operational excellence
- Deep understanding of why data trust timeliness and accuracy are non-negotiable for customer-facing experiences
- Strong collaboration with data science AI/ML security and business teams
- Focus on building reliable production-grade data platforms that the entire organization can depend on
TekWissen Group is an equal opportunity employer supporting workforce diversity.
