Databricks Data Engineer / Business Analyst - Open Contracting Data Standard (OCDS)
Position Summary Scicom Infrastructure Services is seeking a Data Engineer / Business Analyst to support a large-scale Databricks implementation. This hybrid role will bridge business, contracting, data-governance, and engineering teams to define business requirements, construct data contracts, map source data, and develop reliable Databricks data pipelines. The successful candidate must have hands-on experience with the Open Contracting Data Standard (OCDS) and understand how contracting and procurement information is structured across planning, tender, award, contract, and implementation stages. OCDS provides a standardized model for publishing and analyzing data throughout the public-contracting process and uses defined schemas, codelists, releases, records, and packages. This individual will work closely with business stakeholders, procurement subject-matter experts, data architects, Databricks engineers, governance teams, and program leadership to translate complex business and contracting requirements into enforceable technical specifications and production-ready data products.
Key Responsibilities
Data Contracts and Business Analysis · Lead requirements-gathering sessions with procurement, contracting, program, analytics, governance, and technical stakeholders. · Define, construct, document, and maintain data contracts between data producers and consumers. · Establish data-contract requirements covering: o Dataset purpose and ownership o Source and target systems o Schemas, fields, and data types o Required and optional attributes o Business definitions and transformation rules o Data-quality expectations o Validation and reconciliation rules o Refresh frequency and delivery schedules o Versioning and schema-evolution requirements o Security classifications and access controls o Service-level expectations o Issue ownership and change-management procedures · Translate business requirements into user stories, acceptance criteria, process flows, data mappings, interface specifications, and technical requirements. · Conduct source-system analysis, data profiling, gap assessments, and source-to-target mapping. · Identify differences between existing procurement data and required OCDS structures. · Facilitate agreement among data owners, producers, consumers, architects, and governance teams. · Maintain traceability from business requirements through data models, engineering implementation, testing, and acceptance. · Evaluate requested changes for downstream effects on data products, reports, integrations, and analytical use cases. · Support backlog refinement, sprint planning, demonstrations, testing, and stakeholder acceptance. OCDS Responsibilities · Apply the Open Contracting Data Standard to procurement and public-contracting datasets. · Map source-system data to appropriate OCDS fields and structures. · Work with data across the contracting lifecycle, including: o Planning o Tender o Award o Contract o Implementation · Develop and maintain mappings for OCDS releases, records, release packages, record packages, identifiers, organizations, parties, items, milestones, documents, transactions, amendments, and related contracting elements. · Interpret and apply OCDS schemas, codelists, validation rules, and implementation guidance. · Determine whether standard OCDS fields meet project requirements or whether documented extensions are necessary. · Support the construction of complete contracting records from multiple transactional releases. · Establish rules for handling amendments, updates, cancellations, corrections, and historical changes. · Validate transformed data against applicable OCDS JSON schemas. · Identify missing, invalid, inconsistent, or nonconforming procurement data and work with stakeholders to resolve deficiencies. · Document assumptions, business rules, mappings, extensions, and exceptions. · Support the publication, exchange, analysis, or internal use of standardized contracting data. Databricks Data Engineering · Design, develop, test, and maintain data pipelines using Databricks, Apache Spark, PySpark, Python, and SQL. · Build ingestion and transformation pipelines for structured and semi-structured procurement data. · Process JSON, CSV, XML, Parquet, relational database, API, and file-based data sources. · Implement Bronze, Silver, and Gold data layers using medallion architecture. · Build normalized, dimensional, analytical, and OCDS-aligned data models. · Use Delta Lake capabilities for schema enforcement, schema evolution, versioning, auditability, and reliable processing. · Develop reusable frameworks for mapping source procurement data into OCDS-compatible outputs. · Implement batch and incremental ingestion patterns. · Use Databricks Workflows, notebooks, jobs, Auto Loader, Delta Live Tables or Lakeflow capabilities, as appropriate. · Develop REST API integrations for source ingestion and downstream data delivery. · Implement automated data-quality, reconciliation, completeness, and conformity checks. · Support Unity Catalog implementation for metadata, ownership, lineage, access control, and data discovery. · Optimize Spark jobs, SQL queries, clusters, partitioning, file sizes, and data layouts. · Participate in code reviews, automated testing, CI/CD, deployment, monitoring, and production support. · Investigate pipeline failures, data discrepancies, and performance issues. Data Quality and Governance · Define measurable quality rules for accuracy, completeness, validity, timeliness, consistency, and uniqueness. · Develop validation controls for required OCDS fields, identifiers, dates, amounts, currencies, organizations, classifications, and contracting relationships. · Create dashboards or reports that show data-contract compliance and data-quality results. · Establish processes for detecting and managing schema drift. · Document data lineage from original procurement systems through Databricks transformations and downstream products. · Work with governance teams to assign data owners, stewards, classifications, retention requirements, and access policies. · Ensure sensitive procurement and supplier information is handled according to security and privacy requirements. · Support auditability through documented rules, version-controlled mappings, validation results, and change histories. Required Qualifications · Bachelor’s degree in computer science, information systems, data analytics, business analysis, engineering, public administration, supply-chain management, or a related field. · At least five years of combined data-engineering, data-analysis, business-analysis, or data-integration experience. · Hands-on experience implementing or working with the Open Contracting Data Standard. · Demonstrated experience constructing, documenting, negotiating, or maintaining data contracts. · Experience mapping procurement or contracting data to OCDS schemas. · Strong knowledge of OCDS releases, records, schemas, codelists, identifiers, contracting stages, and validation practices. · At least three years of hands-on experience with Databricks. · Strong experience with: o Apache Spark o PySpark o Python o SQL o Delta Lake o ETL and ELT pipelines o Data modeling o JSON and JSON Schema o REST APIs o Data-quality validation o Source-to-target mapping · Experience gathering requirements and translating them into implementable engineering specifications. · Ability to communicate effectively with technical and nontechnical stakeholders. · Experience writing user stories, acceptance criteria, business rules, data dictionaries, interface specifications, and process documentation. · Strong analytical, troubleshooting, facilitation, and documentation skills. · Experience working within Agile delivery teams. Preferred Qualifications · Experience with government procurement, public-sector contracting, grants, acquisition, supplier, or financial data. · Experience implementing OCDS extensions or tailoring OCDS for specific organizational requirements. · Familiarity with procurement classifications, organizational identifiers, tender processes, awards, amendments, milestones, transactions, and contract implementation. · Databricks Certified Data Engineer Associate or Professional certification. · Experience with Unity Catalog, Delta Live Tables, Lakeflow, Databricks Workflows, or Structured Streaming. · Experience with Microsoft Azure, AWS, or Google Cloud. · Experience with Azure Data Factory, ADLS Gen2, AWS Glue, Amazon S3, Snowflake, dbt, Kafka, Airflow, or Power BI. · Experience using JSON Schema validation tools and automated data-quality frameworks. · Knowledge of metadata management, master-data management, data lineage, and reference-data governance. · Experience with CI/CD, Git, Azure DevOps, GitHub Actions, Jenkins, or Terraform. · Experience supporting large federal, state, local-government, or regulated-enterprise data programs. · Familiarity with federal acquisition, procurement, reporting, transparency, or open-data requirements. Core Competencies · Ability to operate equally well in technical engineering and business-analysis discussions. · Strong understanding of how data contracts create accountability between data producers and consumers. · Ability to convert complex procurement processes into clear data structures and transformation rules. · Attention to detail when interpreting schemas, codelists, business definitions, and validation requirements. · Strong stakeholder-facilitation and conflict-resolution skills. · Ability to identify gaps and ambiguities before they become engineering defects. · Commitment to documentation, traceability, governance, and data quality. · Ability to work effectively within a large, multidisciplinary Databricks team.