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Senior Data Engineer
- Saint Paul, Illinois, United States
- Saint Paul, Illinois, United States
Über
We are seeking a Senior Data Engineer to join our growing Data & Analytics practice. This is a client‑facing, consultative role for someone who combines strong technical expertise with the ability to build trust, influence decisions, and help shape winning solutions.
In this role, you will architect and deliver modern data platforms that power analytics, AI/ML, and business intelligence initiatives. You’ll work closely with client stakeholders, data scientists, and engineering teams to design scalable, secure, and high‑performing data solutions across a variety of cloud and data technologies.
What You’ll Do
Design and build scalable, end‑to‑end data pipelines across structured, semi‑structured, and unstructured data sources
Support sales process for data‑centric solutions
Implement modern data architectures (e.g., lakehouse, data warehouse, data mesh) with strong data quality, governance, and security practices
Develop and optimize ETL/ELT pipelines using modern data platforms (e.g., Databricks, Snowflake, Microsoft Fabric, or similar)
Tune and optimize workloads for performance and cost efficiency across cloud‑based data platforms
Implement real‑time and streaming data solutions (Kafka, Kinesis, Event Hubs, or similar)
Enable AI/ML use cases by building data pipelines for feature engineering and model integration
Partner with client stakeholders to translate business needs into scalable technical solutions—and contribute to shaping solution strategy during engagements
Contribute to DevOps best practices including CI/CD and infrastructure‑as‑code (e.g., Terraform)
Mentor junior engineers and contribute to practice development and thought leadership
What You Bring
5+ years of experience in data engineering or modern data platform development
Strong experience designing and building scalable data solutions in a cloud environment
Expertise in SQL, data modeling, and modern data architecture patterns, medallion architecture
Experience with at least one major cloud platform (Azure preferred; AWS or GCP acceptable)
Hands‑on experience with ETL/ELT frameworks and orchestration tools (Airflow, dbt, ADF, or similar)
Familiarity with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent technologies
Solid understanding of DevOps practices for data, including CI/CD and infrastructure‑as‑code
Strong communication and interpersonal skills, with the ability to operate effectively in client‑facing environments
Ability to balance hands‑on development with solution design and technical leadership
Nice to Have
Experience with Databricks and/or Spark‑based data processing
Databricks certifications
Experience with Snowflake
Snowflake certifications
Experience with Microsoft Fabric
Microsoft certifications (e.g., Azure, Fabric‑related certifications such as DP-600)
Programming experience in Python or Scala
Experience with enterprise data governance tools and frameworks
Familiarity with vector databases and semantic search applications
Experience supporting AI/ML workflows and cloud‑based ML services
Cloud certifications (Azure, AWS, or GCP)
Experience with BI tools such as Power BI, Tableau, or Looker
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Sprachkenntnisse
- English
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