Autonomously perform business analysis for data-based use cases, including direct interaction with SMEs, early data investigation, and phased design planning.
Create accurate entity mappings for data integrations and transformations, including business rules.
Develop entity relationship diagrams to document data development cases: process flows, source-to-target mappings, and database structures.
Define project scope, approach, and next steps, ensuring alignment with business and technical objectives in consultation with technical leads.
Determine appropriate data staging frequency and mode (e.g., near-real-time streaming, daily wipe-reload).
Define data provisioning methods, such as file-based, analysis tables, or visualizations.
Data Analysis(25%)
Analyze incoming data from various sources (raw datasets, tables, APIs, etc.) to understand potential, issues, and transformation needs.
Independently perform data cleanup and profiling to detect anomalies, alignments, and patterns.
Infer likely data rules and confirm unknown concepts with domain owners.
Understand and apply AI tools and pretrained models for daily data analysis tasks.
Provide L3/L4 support for production data issues, with advanced query capabilities and ETL troubleshooting skills.
Lead contracted resources in resolving production data issues.
Data Development(50%)
Design and develop data solutions from prototype to production, including ETLs, integrations, analyses, limited data apps, and visualizations.
Automate pipelines using scripting and ETL tools.
Monitor and manage pipeline execution; implement error handling and orchestration jobs.
Perform and oversee data migration analysis, mapping, execution, and troubleshooting.
Apply ACID principles and data load strategies (wipe/reload, upsert, CDC) based on scenario and latency.
Lead contract resources in executing design and development of data products.
Ensure overall quality of delivered data solutions.
Apply Agile concepts (e.g., MVP, fail fast); actively participate in project ceremonies such as daily stand-ups and sprint reviews.
Take ownership of assigned tasks; create and delegate subtasks appropriately.
Author technical documentation, including design specifications, installation guides, and deployment notes.
Conduct thorough unit testing, peer reviews, and regression testing.
Design, execute, and supervise test script execution and automation.
Manage deployment and hypercare activities.
Data Architecture(10%)
Identify and relate key VMRD data entities to enhance cross-use case linkability.
Acquire and apply additional metadata for VMRD entities.
Apply Master Data Management (MDM) principles.
Ensure data security in apps, visualizations, databases, and file systems.
Implement role-based security and manage sensitive data, including PII and IP.
Understand GxP implications in technical systems and processes.
Collaborate with Systems Engineers on app-related projects.
Contribute to continuous improvement of process and knowledge sharing.
ORGANIZATIONAL RELATIONSHIPS
ZTD R&D Solution Partners
ZTD R&D Systems Engineers
ZTD Centers of Excellence
VMRD Business SMEs across multiple product lines and departments
RESOURCES MANAGED
Technical direction for 0–4 contingent workers
EDUCATION AND EXPERIENCE
Undergraduate degree in Information Technology, Computer Science, or related field (or equivalent education/work experience).
5–8+ years in data application design, development, and support (3–6+ with Master's degree).
Experience working with multiple vendors and departments for service/support.
Strong interpersonal and communication skills to build effective relationships.
Experience coordinating with distributed and cross-functional teams across time zones.
Skilled in prioritizing and progressing through ambiguity.
TECHNICAL SKILLS REQUIREMENTS
Knowledge of structured and unstructured data practices.
Strong understanding of data structuring for analytics and data science.
Extensive experience with ETL tools (e.g., Alteryx, Python, Informatica, Databricks).
Proficiency in scripting languages (Python, PowerShell, R).
Working knowledge of SQL Server, Oracle, T-SQL, and PL/SQL.
Strong SQL query writing and troubleshooting expertise.
Basic statistics and data profiling capabilities.
Experience with visualization tools (Power BI, Tableau) and Microsoft Excel.
Use of pretrained GenAI tools to accelerate development.
Familiarity with unit, integration, and regression testing.
Skilled in technical documentation aligned with SDLC standards.
PROJECT MANAGEMENT SKILLS
Experience with Solution Delivery Lifecycle Management.
Proficient in Agile, with familiarity in Waterfall methodologies.
Able to self-manage targeted projects and delegate tasks effectively.
