Data Engineering- Austin TX | W2

Data Engineering-  Austin TX

Interveiw - virtual

Onsite Role

 Notes from manager:
Heavy Databricks
- relational tables that get injested to databricks
-some BI
***Manufacturing or IOT Telemerty data experience would be a HUGE plus
*** Vehicle teletry data would also work
Key Technical Requirements

• Strong hands-on experience with Databricks and Medallion Architecture, including Bronze, Silver, and Gold data layers.
• Experience designing and implementing data ingestion and transformation pipelines in Databricks.
• Strong understanding of Change Data Capture (CDC) concepts and implementation for incremental data processing.
• Hands-on experience with CDC and data replication tools, including Oracle Golden-Gate and related transaction/log-based capture mechanisms.
• Experience integrating CDC data into Databricks/Spark-based data pipelines and handling inserts, updates, deletes, and incremental loads.
• Strong proficiency in Python and PySpark for data engineering, transformation, cleansing, aggregation, and large-scale data processing.
• Ability to explain the complete source-to-target data flow, including data capture, ingestion, transformation, validation, and loading into downstream systems.
• Hands-on experience troubleshooting data ingestion failures, CDC issues, data quality problems, and pipeline performance bottlenecks.
• Candidates must be able to clearly explain the tools used, their purpose, implementation approach, and their personal hands-on contribution in previous projects.

Need a problem solver that is not afraid to ask for help. some of the work requires this person going to various orgs within GM to get answers. 
 

Job Summary

We are seeking a contract Data Engineer to support a program focused on data analytics, data engineering, Databricks, and AI/analytics capabilities. Approximately 80% of the role will focus on engineering and correlating data from multiple source systems to provide trusted context for a target system and its AI functions. The remaining 20% will support BI activities using Power BI and/or Databricks Dashboards.
The contractor must work mostly independently with minimal guidance, translate high-level requirements into actionable solutions, and bring clarity to ambiguous problems.

Job Responsibilities

• Develop data pipelines, transformations, curated datasets, and analytical data products using Databricks and related technologies.
• Learn and interpret data models, definitions, relationships, and quality characteristics across multiple source systems.
• Correlate and integrate data to create comprehensive, trusted context for operational, AI, and advanced analytics use cases.
• Translate high-level or ambiguous requirements into clear technical approaches, assumptions, work plans, and outcomes.
• Identify data gaps, dependencies, risks, and quality issues; drive stakeholder alignment and resolution.
• Document data models, source-to-target mappings, transformation logic, lineage, and assumptions.
• Develop and maintain BI dashboards and visualizations using Power BI and/or Databricks Dashboards.
• Collaborate with data owners, subject-matter experts, engineers, and program stakeholders while owning deliverables from discovery through implementation.
• Support testing, deployment, troubleshooting, monitoring, and continuous improvement.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Analytics, or a related field, or equivalent experience.
• Experience in data engineering, data analytics, or a related technical role.
• Hands-on experience with Databricks, SQL, and Python, PySpark, or comparable data engineering tools.
• Experience integrating and correlating data from multiple source systems and working with complex data models.
• Experience developing data pipelines, transformations, curated data layers, or analytical data products.
• Experience with Power BI and/or Databricks Dashboards.
• Familiarity with data quality, governance, metadata, lineage, and documentation practices.
• Experience supporting AI, machine learning, or advanced analytics use cases is preferred.
• Demonstrated ability to work independently, exercise sound judgment, and deliver with very little guidance.
• Strong problem-solving and communication skills, including the ability to create clarity from high-level requirements and drive cross-functional alignment.