Senior Data Engineer – Enterprise Data Warehouse

Location: Pittsburgh

Job Type: Full Time / Permanent

We are looking for an experienced Sr. Data Engineer to focus on improving the availability and quality of data that is made available throughout the organization with specific attention to a particular domain critical to the success of the organization. In this role, you will develop deep knowledge and understanding of the data assets available within our data platforms and act as the subject matter expert on the data and its utility for operational use. While joining forces with the business, data engineering employees and product development partners, your expertise in petabyte scale data in data lakes, data warehouses or data marts ­– in structured, semi-structured and unstructured formats – will deliver on the Data and Analytics organization’s mission to enable data-driven decisioning within any action. Joining you along this journey to the best-in-class data footprint will be employees across data science, platform engineering and software development, all with a unified strategy and supporting goals. This role models, implements and nurtures data which ultimately becomes certified or the ‘single source of truth’ for the organization. As such, data stewardship, governance and compliance routines will depend on successful delivery against these objectives.

Job Duties & Responsibilities: Work directly with the developers, system architects, and users to review requirements and deliver best-practice database models. Work with stakeholders including the product, data and architecture teams to assist with data-related technical issues and support their data infrastructure needs. Provide proactive design, operational support, and governance for privacy and security policy for data.

What you will bring: 5-7 years of experience in Data Warehousing and Data Modeling, ETL/ELT,SQL,Python,Kafka,Spark,Airflow Bachelor’s Degree in Library Science, Information Systems, Finance, Information Technology or equivalent experience. Any Public Cloud certification focused on data warehousing. Any certification on specific database technology. Strong understanding of Normalized/Dimensional model disciplines and similar data warehousing techniques. Strong experience working with ETL/ELT concepts of data integration, consolidation, enrichment, and aggregation in petabyte scale data sets. Expert in SQL and/or SQL based languages and performance tuning of SQL queries. Collaborate with Product and analytics teams on normalizing and aggregating large data sets based on business needs and requirements. Data auditing skills to verify data integrity, understand discrepancies and resolve them with the highest sense of urgency. Experience with cloud-based data warehouses – e.g. Snowflake, BigQuery, Synapse, RedShift, etc. Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores (Kafka, Pub/Sub). Experience building data pipelines on modern public cloud services like Snowflake, AWS, GCP, or Azure Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow. Familiarity with Analytical/Reporting Solutions like Qlik Sense, PowerBI is a plus Proficient in Linux/Unix environments.