Overview
On Site
Contract - W2
Skills
Extraction
Cloud Computing
Amazon Web Services
Relational Databases
NoSQL
Business Intelligence
Reporting
Tableau
Microsoft Power BI
Storage
Extract
Transform
Load
Mapping
Machine Learning (ML)
Natural Language Processing
Data Governance
Python
Scala
Java
SQL
Snow Flake Schema
Microsoft SQL Server
Oracle
MongoDB
Financial Services
Health Care
Real-time
Data Engineering
Meta-data Management
Artificial Intelligence
Job Details
Collibra Data Lineage Automation Engineer
McLean, VA
6+ months
Role is on-site in McLean 5 days per week
We are seeking a highly experienced Data Lineage Automation Engineer to lead the design and implementation of automated end-to-end lineage solutions across a highly heterogeneous enterprise data ecosystem. This role requires deep technical expertise in lineage frameworks (such as Spline and OpenLineage), experience across cloud and legacy environments, and a strong AI foundation to support intelligent metadata extraction and traceability.
Key Responsibilities Lead the implementation of automated data lineage across a complex data estate that includes: o Cloud platforms (e.g., Snowflake, AWS) o Legacy relational databases and ETLs o NoSQL data stores o BI/reporting platforms (e.g., Tableau, Power BI) Implement or extend frameworks such as Spline, OpenLineage, or similar open frameworks to support active lineage capture Build connectors, extractors, or agents where necessary to bridge gaps between systems and lineage frameworks Integrate with metadata platforms (e.g., Collibra) to publish lineage in a consumable format Apply AI/ML techniques to infer lineage where automation is incomplete (e.g., handling Java based ETLs), using logs, query patterns, or usage metadata Develop reusable lineage components for operational reuse across domains Guide stakeholders on best practices for lineage standardization, storage, and use
Required Skills & Experience Proven experience delivering automated data lineage solutions across hybrid architectures Hands-on expertise with Spline, OpenLineage, Marquez, or comparable lineage frameworks Deep understanding of metadata capture, ETL process tracing, and query execution mapping Strong AI/ML background particularly in metadata intelligence, natural language processing for code parsing, or pattern detection Experience integrating lineage with data governance tools (e.g., Collibra, Alation, etc.) Strong programming background in Python, Scala, or Java Deep familiarity with SQL and query logs from systems like Snowflake, SQL Server, Oracle, MongoDB, etc.
Big Plus Skills Experience with third-party commercial data lineage solutions a plus (evaluations and implementations) Prior work in regulated environments (e.g., financial services, healthcare) Familiarity with event-based architectures for real-time lineage propagation Knowledge of data mesh or domain-driven lineage strategies
Ideal Candidate Has successfully implemented automated lineage at enterprise scale Operates at the intersection of data engineering, metadata management, and AI Can act as a technical thought partner to architecture teams and governance leads Brings the mindset of automation-first and reuse-oriented design
McLean, VA
6+ months
Role is on-site in McLean 5 days per week
We are seeking a highly experienced Data Lineage Automation Engineer to lead the design and implementation of automated end-to-end lineage solutions across a highly heterogeneous enterprise data ecosystem. This role requires deep technical expertise in lineage frameworks (such as Spline and OpenLineage), experience across cloud and legacy environments, and a strong AI foundation to support intelligent metadata extraction and traceability.
Key Responsibilities Lead the implementation of automated data lineage across a complex data estate that includes: o Cloud platforms (e.g., Snowflake, AWS) o Legacy relational databases and ETLs o NoSQL data stores o BI/reporting platforms (e.g., Tableau, Power BI) Implement or extend frameworks such as Spline, OpenLineage, or similar open frameworks to support active lineage capture Build connectors, extractors, or agents where necessary to bridge gaps between systems and lineage frameworks Integrate with metadata platforms (e.g., Collibra) to publish lineage in a consumable format Apply AI/ML techniques to infer lineage where automation is incomplete (e.g., handling Java based ETLs), using logs, query patterns, or usage metadata Develop reusable lineage components for operational reuse across domains Guide stakeholders on best practices for lineage standardization, storage, and use
Required Skills & Experience Proven experience delivering automated data lineage solutions across hybrid architectures Hands-on expertise with Spline, OpenLineage, Marquez, or comparable lineage frameworks Deep understanding of metadata capture, ETL process tracing, and query execution mapping Strong AI/ML background particularly in metadata intelligence, natural language processing for code parsing, or pattern detection Experience integrating lineage with data governance tools (e.g., Collibra, Alation, etc.) Strong programming background in Python, Scala, or Java Deep familiarity with SQL and query logs from systems like Snowflake, SQL Server, Oracle, MongoDB, etc.
Big Plus Skills Experience with third-party commercial data lineage solutions a plus (evaluations and implementations) Prior work in regulated environments (e.g., financial services, healthcare) Familiarity with event-based architectures for real-time lineage propagation Knowledge of data mesh or domain-driven lineage strategies
Ideal Candidate Has successfully implemented automated lineage at enterprise scale Operates at the intersection of data engineering, metadata management, and AI Can act as a technical thought partner to architecture teams and governance leads Brings the mindset of automation-first and reuse-oriented design
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.