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Data Specialist Data Migration, Data Mapping & ETL

InfoPeople Corporation

  • Albany, NY
  • 3 days ago

    Highlights

    Perform Extract Transform & Load (ETL) and related activities including developing strategies for extracting, transforming, and loading data from the As-Is system into To-Be system and data warehouse/DataMart. The primary focus of this role is to deliver complete, well-documented, and validated source-to-target data mapping requirements along with development and testing effort of the solution.

    Numbers & Facts

    LocationAlbany, NY

    Description

    Job Description: Data Specialist (Level III)
    Role Summary
    We are looking for an experienced Data Specialist to own the data mapping, and data requirements work for our system migration. The primary focus of this role is to deliver complete, well-documented, and validated source-to-target data mapping requirements along with development and testing effort of the solution.
    Key Responsibilities
    • Work with Subject Matter Experts, Business Analysts, and Development Teams to gather, define, and document data requirements and attributes for the project.
    • Develop and maintain As-Is to To-Be source-to-target data mapping, including analysis and interpretation of complex data on both source and target systems.
    • Document To-Be target model data requirements based on business requirements and validate them with stakeholders.
    • Perform Extract Transform & Load (ETL) and related activities including developing strategies for extracting, transforming, and loading data from the As-Is system into To-Be system and data warehouse/DataMart.
    • Developing and testing UNIX Shell Scripting.
    • Perform source system metadata analysis, documentation, and validation.
    • Define and document data profiling, data cleansing, and data transformation rules.
    • Coordinate and facilitate data profiling and data cleansing activities with business users.
    • Interpret data profiling results and present findings and recommendations in a clear, concise manner.
    • Gather, analyze, and document data synchronization and bridging requirements.
    • Identify and resolve data quality and consistency issues, and support data conversion quality assurance testing.
    • Develop and test SQL queries against databases such as Oracle and SQL Server to analyze and validate data.
    • Other duties as assigned.


    Mandatory Qualifications:

    1. Level III- More than seven (7) years of experience working on complex projects with 2 or more years in a leadership role as a Specialist
    2. More than seven (7) years working on data conversion/data warehouse projects, including: source system metadata analysis, documentation, and validation; source-to-target data mapping; data profiling and data cleansing rules; To-Be system data requirements gathering, analysis, documentation, and validation; data synchronization and bridging requirements; and data conversion quality assurance testing; experience with UNIX shell scripting with performance tuning of queries during data loads and transformations.
    3. More than seven(7) years of experience working across the full Software Development Life Cycle (SDLC) for data conversion/data warehouse projects, including requirements gathering, design, development, testing, and deployment phases as a Data Analyst and ETL developer in data warehousing or data integration projects; writing SQL statements and queries against RDBMS platforms such as Oracle, SQL Server, and PostgreSQL as part of development and validation; developing and executing ETL processes using any industry-standard ETL tool or scripting-based approach (e.g., Informatica, T-SQL, PL/SQL, PL/pgSQL).

    Desirable Qualifications:
    1. Three or more years of experience in government or public sector data systems.
    2. Experience with data conversion/migration projects, especially legacy-to-modern system transitions .
    3. Strong understanding of data warehouse/DataMart concepts (staging, dimensional modeling, etc.)
    4. Five or more years of experience with Data Quality processes, approaches, measurement techniques, and business cases for data profiling, cleansing, standardization, and match and merge functionality.
    5. Working knowledge of Python for data processing or automation scripts, a plus.
    6. Experience supporting QA/UAT for data conversion testing.
    7. Strong written and verbal communication skills; ability to present data findings to technical and non-technical audiences.
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