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: - Dataset purpose and ownership - Source and target systems - Schemas, fields, and data types - Required and optional attributes - Business definitions and transformation rules - Data-quality expectations - Validation and reconciliation rules - Refresh frequency and delivery schedules - Versioning and schema-evolution requirements - Security classifications and access controls - Service-level expectations - 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: - Planning - Tender - Award - Contract - 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: - Apache Spark - PySpark - Python - SQL - Delta Lake - ETL and ELT pipelines - Data modeling - JSON and JSON Schema - REST APIs - Data-quality validation - 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.

Databricks Data Engineer / Business Analyst – Data Contracts & OCDS

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