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Data Engineer

Hybrid in Louisville, KY, US • Posted 9 hours ago • Updated 9 hours ago

Full Time

No Travel Required

Hybrid

$110,000 - $120,000/yr

Fitment

Dice Job Match Score™

🎯 Assessing qualifications...

Job Details

Skills

Amazon Web Services
Cloud Computing
Collaboration
Continuous Integration
Data Architecture
Data Engineering
Data Governance
Data Modeling
Data Security
Databricks
Amazon Redshift
Docker
Encryption
Kubernetes
Prototyping
Python
Extract
Transform
Load
Optimization
Snow Flake Schema
SQL
Apache Spark
ELT
Systems Design

Summary

Data Architect:

Locals only who are in the drivable area of Cincinnati although this is primarily a remote job for Louisville KY

Key Responsibilities

Lead end-to-end data solution architecture (data flows, models, and system design).
Define data platform patterns (batch vs streaming, ingestion, storage, processing).
Build prototypes and guide teams in developing scalable data pipelines and models.
Optimize data performance, partitioning, and query efficiency.
Collaborate with business and engineering teams to translate requirements into solutions.
Ensure security, governance, and compliance (IAM, encryption, data quality).
Establish standards, CI/CD practices, and reusable frameworks.
Drive observability, monitoring, and cost optimization for data platforms.

Must-Have Skills & Experience

6+ years in Data Engineering / Data Architecture.
Strong expertise in data modeling (Dimensional, Data Vault, schema design).
Hands-on experience with modern data stack:

Cloud DW: Snowflake / Redshift / BigQuery
Processing: Spark / Databricks / PySpark
Streaming: Kafka / Kinesis

Strong programming in Python (or Scala) + advanced SQL.
Experience building enterprise-scale data pipelines.
Hands-on with ETL/ELT, orchestration tools (Airflow, dbt, etc.).
Experience with cloud platforms (AWS preferred).
Knowledge of IAM, encryption, and data security best practices.
Strong stakeholder communication & architecture decision-making skills.

Nice to Have

Experience with Terraform, Kubernetes, Docker.
Familiarity with data governance tools (lineage, cataloging, data quality).
Certifications (AWS Architect, Databricks, Snowflake, CDMP).
Exposure to observability tools (Datadog, Prometheus).

Success Metrics

Faster delivery of data products to production
Improved data quality & reliability
High system uptime and performance
Adoption of standardized architecture patterns

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10112669
Position Id: PCS222
Posted 9 hours ago

Contact the job poster

Mukul Kumar

Recruiter @ Progressive Computer Solutions

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