Data Success Engineer
Parra Consulting Group
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- Location
- Gaithersburg, MD
- Job type
- Full time
- Posted
- Oct 27
- 1 day ago
Career path
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About the company
Parra Consulting Group
Management consulting · 11 to 50 employees
What you'll do
- Partner with stakeholders to understand business processes and data needs
- Facilitate discussions and translate needs into user stories, mappings, and specifications
- Build and improve data pipelines, including solutions built with Databricks
- Use SQL and Python to query, profile, transform, and validate data
- Troubleshoot data quality issues across multiple tables and sources
- Document data definitions and transformation logic
- Explain technical findings in clear, non-technical language
- Contribute to Agile planning, sprint activities, and continuous improvement
What you need
- Ability to obtain and maintain a Public Trust or Suitability/Fitness determination
- Experience gathering, analyzing, and documenting business or data requirements
- Experience working directly with clients and stakeholders
- Experience with Databricks, data warehousing, lakehouse or medallion architecture (preferred)
- Databricks, AWS, or data engineering certifications (preferred)
- Education: a bachelor's degree
Key skills
SQLPythonAWS GlueAmazon S3Amazon RDSRelational databasesBusiness requirementsData requirementsUser storiesAcceptance criteriaSource-to-target mappingsTechnical specificationsDatabricksAnalyticalCommunication skills
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Read the full posting here
Parra Consulting Group (PCG) is seeking a Data Success Engineer to support a federal client’s enterprise data and analytics program. This position works at the intersection of business analysis and data engineering, partnering with stakeholders to turn mission needs into reliable, usable data products that help people make better decisions.
This successful candidate will be responsible for the following:
Partner with business stakeholders, data owners, analysts, and technical teams to understand business processes and data needs.
Facilitate information-gathering discussions, clarify requirements, and translate needs into user stories, acceptance criteria, source-to-target mappings, and technical specifications.
Build and improve the data pipelines that deliver data to business users, including solutions built with Databricks.
Use SQL and Python to query, profile, transform, and validate data, and troubleshoot data quality issues across multiple tables and sources.
Ensure data solutions meet business requirements and help clients understand how their data products support business outcomes.
Document data definitions and transformation logic, and explain technical findings in clear, non-technical language.
Contribute to Agile planning, sprint activities, and continuous improvement efforts.
Required Qualifications
Bachelor’s degree in Computer Science, Computer Engineering, Engineering, Math, Physics, or Information Systems and Technology.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
S. citizenship required to support this federal contract.
Required Experience
Experience gathering, analyzing, and documenting business or data requirements, including translating needs into user stories, acceptance criteria, source-to-target mappings, or technical specifications.
Experience working directly with clients and stakeholders to facilitate information-gathering discussions, ask effective questions, clarify needs, and communicate findings.
Experience with SQL, including writing complex queries and investigating data issues across multiple tables or sources.
Experience using AWS services, including AWS Glue, Amazon S3, and Amazon RDS.
Experience using Python for data processing, automation, or pipeline development.
Experience working with relational databases and structured data.
Ability to connect business objectives to data requirements and technical implementation.
Preferred Qualifications
Experience with Databricks, including notebooks, Spark, Delta Lake, or Databricks SQL.
Experience with data warehousing, lakehouse architecture, or medallion data architecture.
Experience with data quality frameworks, metadata management, or data governance.
Experience with Agile delivery tools and practices, such as Jira, Confluence, and Scrum.
Experience creating process flows, data models, or other artifacts that help teams understand how data moves and is used.
Strong analytical, problem-solving, written, and verbal communication skills.
Databricks, AWS, or data engineering certifications.