Senior Data Engineer

Responsibilities

• Design, develop, and implement enterprise data engineering solutions to support business processes and analytical needs.
• Collaborate with Business Analysts, Architecture teams, and cross-functional stakeholders to gather requirements and translate them into scalable data models, cloud data pipelines, and integration frameworks.
• Build data integration processes with SAP Data Services, SSIS, and Azure Data Factory to extract, transform, and load structured and unstructured data across heterogeneous systems.
• Develop and optimize data processing platforms using Microsoft Azure services, including Azure Data Factory and Azure SQL Database.
• Design end-to-end ETL and ELT pipelines for ingestion, transformation, and analytical data preparation; implement complex SQL logic, stored procedures, packages, and functions in Oracle and SQL Server.
• Develop and maintain data warehouse and data lake architectures using Star and Snowflake schema designs.
• Perform data profiling and data quality checks, enforcing governance standards to ensure integrity and compliance across the data lifecycle.
• Prototype solution designs for review with business and architecture teams; evaluate and select cloud technologies for ingestion, transformation, reporting, visualization, and analytics.
• Design and develop dashboards, KPIs, and visualizations using Power BI to support enterprise reporting needs.
• Automate manual workflows using Python and Unix shell scripting.
• Troubleshoot data pipeline failures, optimize performance, and resolve data-related issues to minimize business disruption.
• Participate in data architecture discussions, contributing to integration strategies and modernization efforts.
• Prepare technical design documents, mapping specifications, workflow diagrams, and solution architectures; ensure designs align with security and organizational standards.
• Support all phases of the Software Development Lifecycle, including requirements analysis, design, development, testing, deployment, and production support.
• Mentor junior team members, sharing best practices, coding standards, and cloud data engineering methodologies.
• Must reside within a reasonable commuting distance from headquarters and be able to appear in the office as required.

Requirements

• Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a related field, plus five years of progressive post-baccalaureate experience in ETL development or data engineering roles.
• Experience developing and optimizing entity relationship models using ERWIN and crafting advanced SQL queries to support analytics.
• Designing, developing, and tuning enterprise database schemas in Oracle and Microsoft SQL Server, including tables, views, stored procedures, indexing strategies, and performance tuning.
• Building ETL and data integration workflows with SAP Data Services, SSIS, and Azure Data Factory, including pipelines, datasets, triggers, integration runtimes, and source-to-target mapping documents.
• Designing dimensional data models for OLTP and OLAP using Star and Snowflake schemas, applying normalization and denormalization practices.
• Developing automation scripts with Python and Unix shell scripting to streamline ingestion, transformation, validation, and cloud analytics processes.
• Creating interactive dashboards and reports with Power BI for operational and analytical insights.
• Enforcing data integrity, accuracy, and compliance via data quality checks, validation rules, and governance frameworks.
• Implementing data governance and quality processes, including profiling, reconciliation checks, error handling, and anomaly detection.
• Designing and managing scheduling and workflow automation using ADF triggers, Jenkins, SQL Server Agent, or TIDAL to orchestrate ETL and data pipelines.
• Using version control systems such as GitHub or SVN to manage source code and maintain consistency across ETL pipelines and cloud resources.
• Experience across all phases of the Software Development Lifecycle, including requirements gathering, design, development, documentation, testing, deployment, and production support.
• Ability to perform troubleshooting, root cause analysis, and performance optimization of SAP BODS jobs, SQL queries, ADF pipelines, and cloud-based data transformations.

Technologies

• SAP Data Services, SSIS, Azure Data Factory, Azure SQL Database
• Oracle, Microsoft SQL Server, Power BI
• Python, Unix Shell scripting
• ERWIN, GitHub, SVN, Jenkins, SQL Server Agent, TIDAL
• SAP BODS, Star schema, Snowflake schema

Benefits

• Competitive base pay plus incentive compensation
• 401(k) with robust matching and additional contributions
• Comprehensive medical and prescription coverage
• 100 percent employer-paid dental and vision benefits
• Wellbeing program with meaningful financial incentives
• Generous paid time off, plus 12 paid holidays and your birthday off
• Culture focused on growth and learning with career development, tuition reimbursement, and a recognition program
• Family support including adoption assistance, fertility services, and care for children, elders, and pets
• Opportunities for social responsibility and volunteer involvement
• Employee discount program