Job Title
- Data Engineer Job Location Locals only (can work remote but HAVE to still live locally, no relo exceptions), Louisville, KY 40202
- Onsite from day one
- -Need to be local End Client
Client Industry:
Insurance Duration- 6 Months+ C2H Mode Of Interview F2F/onsite final round, other rounds via MS Teams Video Note
- Need LinkedIn Does this candidate have a high school diploma/GED or equivalent Data Architect leading end-to-end design and delivery of enterprise data platforms and data products aligned to business use cases.
Owns solution architecture including data flows, system design, and selection of patterns (batch vs streaming, ingestion, storage, processing). Provides hands-on technical leadership by building prototypes, guiding development, and optimizing data models, pipelines, and query performance. Defines reusable architecture patterns, accelerators, and standards across the data domain. Partners with Product Owners, Engineering, Security, and business stakeholders to translate requirements into scalable solutions. Ensures security, compliance, and governance through IAM, encryption, data masking, lineage, and metadata standards. Drives operational excellence with SLOs, monitoring, observability, data quality frameworks, and incident management. Supports roadmap planning, cost optimization, and platform alignment while influencing enterprise architecture strategy.
Requirements:
6+ years of experience in data engineering, data architecture, or similar roles building enterprise-scale data platforms. Strong expertise in data modeling (dimensional, data vault, canonical), schema design, and query optimization. Hands-on experience with modern data stack: Snowflake, Redshift, BigQuery, Databricks/Delta Lake, Spark/PySpark. Experience with streaming technologies (Kafka, Kinesis) and large-scale data processing. Strong programming skills in Python and/or Scala, plus advanced SQL. Experience with orchestration and CI/CD tools (Airflow, dbt, Prefect, Jenkins, GitHub Actions) and Infrastructure as Code (Terraform, CloudFormation). Cloud experience (AWS preferred; Azure/Google Cloud Platform acceptable) and familiarity with Kubernetes and Docker. Strong knowledge of security and governance (IAM, encryption, tokenization, row/column-level security, data lineage tools). Experience with observability and data quality tools (Datadog, Prometheus, Great Expectations, Monte Carlo). Strong communication and stakeholder management skills with ability to explain technical concepts to non-technical audiences.
Preferred:
Certifications such as AWS Solutions Architect, Databricks, Snowflake, CDMP, or security certifications (CISSP, CCSP). Experience influencing enterprise architecture and driving standardization across teams.
