Senior Data Engineer

Job Title: Senior Data Engineer
Location: Orlando FL
Work Type: Hybrid (3-Days onsite)
Job Type: Contract (6-month Contract with potential for extension)
Rate: $55/hr on C2C

Notes:

• Client is looking to move very fast on this
• Prefer local to Orlando will consider relo for a rockstar
• Final interview will be on-site for local candidates
• Must have strong DataStage experience with banking
• Skills Needed: DataStage ETL Development (Data Mapping and Transformation Implementation) Strong SQL Server w/ advanced T-SQL File Based Ingestion etc.

Role summary Software Engineer with strong ETL experience to design build and support file-to-table data transformations using IBM InfoSphere DataStage. Youll turn inbound file feeds into reliable auditable SQL Server table loads with solid performance clear error handling and repeatable operations.

Key responsibilities

• Design develop and maintain IBM DataStage ETL jobs that ingest file feeds (CSV fixed-width delimited) and load curated destination tables in SQL Server.
• Build end-to-end ETL flows including staging transformations validations and publishing to downstream schemas.
• Perform source-to-target mapping and implement transformation logic based on business and technical requirements.
• Use common DataStage stages and patterns (e.g. Sequential File Transformer Lookup Join/Merge Aggregator Sort Funnel Remove Duplicates) with attention to partitioning and parallel job design.
• Write optimize and tune SQL Server queries stored procedures and T SQL scripts used in ETL workflows.
• Implement restartable and supportable jobs: parameterization robust logging reject handling auditing columns and reconciliation checks.
• Apply data quality controls (format checks referential checks null/duplicate checks threshold checks) and produce clear exception outputs for remediation.
• Monitor and troubleshoot ETL runs using DataStage Director/Operations Console and SQL Server tooling; perform root-cause analysis and fix defects.
• Improve performance through job design tuning (partitioning strategy sorting choices buffering pushdown where appropriate) and SQL tuning (indexes statistics set-based logic).
• Participate in code reviews testing documentation and release activities; maintain clear runbooks and operational procedures.
• Collaborate with business analysts data modelers QA and production support to deliver stable pipelines.

Required skills and experience

• Hands-on IBM DataStage ETL development experience including data mapping and transformation implementation.
• Strong SQL Server experience with advanced T SQL (joins window functions CTEs temp tables indexing basics query plans).
• Solid understanding of file-based ingestion and parsing (CSV fixed-width headers/trailers control totals encoding delimiters quoting/escaping).
• Experience designing ETL jobs with good operational characteristics: parameter-driven design logging error handling restart/re-run strategy and auditability.
• Ability to troubleshoot data issues end-to-end (source file stage tables target tables) and communicate findings clearly.

Preferred qualifications

• Experience with DataStage Parallel Jobs tuning (partitioning methods collect/sort trade-offs skew handling).
• Familiarity with UNIX/Linux basics and shell scripting for orchestration and file handling.
• Experience with job scheduling/orchestration tools (e.g. Control M Autosys) and CI/CD practices.
• Knowledge of common warehousing patterns (incremental loads slowly changing dimensions surrogate keys effective dating).
• Experience with version control (Git) and structured promotion/release processes across environments (dev/test/prod).
• Exposure to data governance practices (metadata lineage naming standards) and secure handling of sensitive data.

Education

• Bachelors degree in Computer Science Engineering Information Systems or equivalent practical experience.

What success looks like in this role

• File feeds land and load consistently with clear reconciliation results.
• Failures are diagnosable from logs and reject outputs without deep forensics.
• Jobs meet runtime SLAs through solid DataStage design and SQL tuning.
• Mappings and transformations are documented and traceable to requirements.