Data Engineer- SQL ZTD R&D

POSITION RESPONSIBILITIES(100%)

Business Analysis(15%)

• 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.

PHYSICAL POSITION REQUIREMENTS

• Occasional travel: 0–5%