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Remote Director Data Engineering Jobs in Elizabethtown, KY

DemandFactor is a data-driven B2B growth and demand-generation company helping brands find, engage ... We're looking for a Marketing Director to build and scale our marketing function. This is a hands ...

This position is remote and/or hybrid-friendly and can be performed from a wide range of locations ... Analyze and review project work products, including technical data, engineering calculations ...

Collaborate with engineers, operations, and project teams to ensure data accuracy * Contribute to ... Able to work independently in a remote environment * Willing to travel 25%+ to sites or industry ...

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Remote Director Data Engineering information

See Elizabethtown, KY salary details

$67K

$178.7K

$233.2K

How much do remote director data engineering jobs pay per year?

As of Sep 1, 2026, the average yearly pay for remote director data engineering in Elizabethtown, KY is $178,733.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,900.00 and $232,200.00 per year, depending on experience, location, and employer.

What job categories do people searching Remote Director Data Engineering jobs in Elizabethtown, KY look for?

The top searched job categories for Remote Director Data Engineering jobs in Elizabethtown, KY are:

What cities near Elizabethtown, KY are hiring for Remote Director Data Engineering jobs?

Cities near Elizabethtown, KY with the most Remote Director Data Engineering job openings:

Infographic showing various Remote Director Data Engineering job openings in Elizabethtown, KY as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $178,733 per year, or $85.9 per hour.

Databricks Developer (Remote)

Delan Associates, Inc

Louisville, KY • Remote

Full-time

Posted 6 days ago


Job description

We are looking for a highly skilled Databricks Developer with expertise in building and managing modern data platforms using the Databricks Lakehouse architecture. The ideal candidate will have strong experience in PySpark, Python, SQL, Delta Lake, data modeling, data quality frameworks, and enterprise-scale data engineering solutions. The role involves designing, developing, and optimizing scalable data pipelines that support analytics, reporting, and AI/ML initiatives.

Key Responsibilities

Design and implement scalable data solutions using Databricks Lakehouse Architecture.

Develop and maintain data pipelines using PySpark, Python, and SQL.

Build and optimize ETL/ELT workflows for batch and near real-time data processing.

Implement Delta Lake features including ACID transactions, time travel, schema evolution, and data versioning.

Design and maintain enterprise data models to support reporting and analytics requirements.

Ensure data quality through validation, monitoring, reconciliation, and governance controls.

Develop and manage data catalogs, metadata management, and data lineage processes.

Collaborate with business stakeholders, architects, and analytics teams to gather and translate requirements into technical solutions.

Optimize Databricks workloads for performance, scalability, and cost efficiency.

Implement security, access controls, and governance best practices within the Databricks ecosystem.

Support troubleshooting, root cause analysis, and production issue resolution.

Contribute to data platform modernization and cloud migration initiatives.

Required Technical Skills

Databricks

Strong experience with Databricks Architecture and platform administration.

Hands-on expertise in Databricks Lakehouse Architecture.

Deep understanding of Delta Lake concepts and implementation.

Experience with Unity Catalog / Data Catalog and metadata management.

Knowledge of Databricks Workflows, Jobs, Clusters, and Performance Tuning.

Data Engineering

Strong proficiency in PySpark for large-scale data processing.

Advanced Python programming skills.

Expert-level SQL development and query optimization.

Experience in building robust ETL/ELT pipelines.

Strong understanding of data modeling techniques including:

Star Schema

Snowflake Schema

Dimensional Modeling

Data Vault (preferred)

Data Governance & Quality

Experience implementing data quality frameworks and validation checks.

Knowledge of data lineage, metadata management, and governance processes.

Experience with data reconciliation, profiling, and monitoring tools.

Cloud & Platform Experience (Preferred)

Azure Databricks

Azure Data Lake Storage (ADLS)

Azure Data Factory

Azure Synapse Analytics

CI/CD pipelines (Azure DevOps, GitHub Actions)

Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.

4-8 years of experience in Data Engineering and Analytics.

Minimum 3+ years of hands-on experience with Databricks and PySpark.

Experience working in Agile development environments.