Technical Data Analyst (W2 Contract Only)

Hiring,

Greetings from Modern Agile Technologies. 

Position:  Technical Data Analyst
Location: Atlanta, GA / Charlotte, NC / Raleigh, NC (Onsite)
Type:        Contract (W2 Only)

Required Skills:

SAS (Code Analysis & Conversion to Snowflake), Snowflake, SQL, Data Analysis, Data Profiling, Source-to-Target Mapping (MapDocs), Data Validation, Data Reconciliation, Data Lineage, Data Governance, ETL Tools (Talend/Informatica), Reporting & Analytics, Unix/Linux, Python, Power BI/Tableau, Data Warehousing, Agile/Scrum

Additional Skillsets –

·        Snowflake Data Warehouse

·        Hive Query Development

·        SQL & Advanced CTE Development

·        Data Migration & Modernization

·        Data Validation & Reconciliation

·        Database Object Creation & Management

·        Data Modeling

·        Machine Learning Pipeline Enablement

·        SageMaker Integration

·        Performance Optimization

·        Dev/Test/QA Deployment Processes

·        Data Governance & Quality Assurance

Data Analysis & Transformation

• Analyze complex SAS programs, macros, and datasets to understand business logic, data flows, and transformation rules.
• Perform SAS code analysis and support migration/conversion to Snowflake.
• Handle multi-format data ingestion including CSV, JSON, TXT, XML, and Parquet files.
• Interpret and document upstream-to-downstream data transformations across systems.
• Analyze source data structures, relationships, and dependencies to support data integration initiatives.

Source-to-Target Mapping (MapDocs)

• Create, maintain, and enhance Source-to-Target Mapping documents (STMs / MapDocs).
• Define detailed transformation logic, business rules, derivations, and field-level mappings.
• Document data lineage and mapping between source systems, ETL processes, and Snowflake targets.
• Ensure traceability between source systems (SAS/upstream) and target platforms (Snowflake).

Data Quality & Profiling

• Perform data profiling to evaluate completeness, accuracy, consistency, uniqueness, and data distribution patterns.
• Design and implement Data Quality (DQ) checks to ensure data integrity and reliability.
• Proactively identify, analyze, and resolve data quality issues and anomalies.
• Support data quality monitoring and reporting across multiple platforms.

Data Validation & Reconciliation

• Execute end-to-end data validation between source systems and Snowflake.
• Perform record count, aggregate-level, and attribute-level reconciliations.
• Validate data across staging, integration, and reporting layers.
• Support defect analysis, root cause identification, issue remediation, and validation signoff.

ETL Analysis & Support

• Analyze ETL workflows developed using Talend and Informatica.
• Collaborate with ETL developers to understand ingestion and transformation logic.
• Review ETL design documents and validate implementation against business requirements.
• Support ETL testing, deployment validation, and production support activities.

Snowflake & SQL Analysis

• Develop and execute complex SQL queries for analysis, reconciliation, and validation.
• Analyze Snowflake schemas, tables, views, and data models.
• Support Snowflake data validation, performance analysis, and optimization initiatives.
• Validate source-to-target data movement and transformation accuracy.

Reporting & Monitoring

• Develop and maintain reports and dashboards for operational and business insights.
• Support Power BI/Tableau reporting and analytics initiatives.
• Monitor data pipelines to ensure timely delivery aligned with SLA/OLA commitments.
• Participate in SLA/OLA definition, approvals, monitoring, and performance tracking.

Collaboration & Support

• Collaborate with ETL Developers, Data Engineers, Architects, Business Analysts, and Business Stakeholders.
• Support requirement gathering, data analysis workshops, and impact assessments.
• Support SIT, UAT, production releases, and post-deployment validation activities.
• Clarify business requirements and document functional specifications.
• Validate data accuracy and ensure reporting reliability.
• Coordinate issue resolution with upstream and downstream teams.

Data Governance & Lineage

• Maintain data lineage documentation for audit, compliance, and governance purposes.
• Ensure transparency of data movement across systems and transformations.
• Support metadata management and governance standards.
• Maintain technical and functional documentation for regulatory and operational requirements.
• Ensure adherence to enterprise data governance policies and best practices.