Lead Data Warehouse Engineers

Company Description

Systech Solutions, Inc. is an all-inclusive data and analytics firm specializing in cloud, data engineering, AI, and machine learning solutions. With over 30 years of experience and a global reach, we provide efficient, cost-effective strategies to solve complex business problems at the intersection of data, business, and digital technologies. Our tailored solutions have garnered a customer retention rate of over 90% in the past five years. We excel in various sectors, including finance, retail, manufacturing, healthcare, and insurance, enhancing operations, increasing revenue, and boosting customer satisfaction. Recognized by Inc. Magazine, our skilled team turns challenges into growth opportunities through insightful data and technology practices.

Responsibilities

• Architecting and maintaining the Operational data stores (ODS), Enterprise Data Warehouse (EDW) and associated data intelligence environments including data lakes, data marts, and metadata repositories
• Designing and implementing high performance data movement pipelines using multiple ETL tools (Informatica, Azure Data Factory, SQL Packages, etc) with batch and real-time event data streams
• Developing scalable and re-usable frameworks for ingestion of structured and semi-structured data; and implementing various large-scale settlement and reconciliation frameworks
• Gathering business and information requirements from various product owners across various functional units
• Designing and creating data architecture and data flow diagrams and collaborating with peers to translate requirements into logical and physical data models.
• Conducting design review sessions and communicating design artifacts with stakeholders.
• Ensures database features and capabilities are incorporated into data model designs to optimize performance, resiliency, and scalability.
• Delivering and presenting proofs of concept to of key technology components to project stakeholders and internal technology leaders
• Developing scalable and re-usable frameworks for ingestion of structured and semi-structured data; and implementing various large-scale settlement and reconciliation frameworks
• Leading and coordinating the design and operationalization of Master Data Management and Data Governance initiatives including custom developed solutions.
• Working with other members of the project team to support delivery of additional project components associated with cloud data platform.
• Problem-solving of Data warehouse and ODS application issues and production errors, including high level critical production issues that require immediate attention.
• Perform other duties as assigned including major new project initiatives.

Qualifications

• Bachelor's and/or Master's degree in Computer Science, Computer Engineering or related field preferred
• 8+ years of overall software development experience is required primarily with Data warehouse applications.

· years of hands-on development experience in Cloud-based data warehouse platform – primarily AWS Redshift

· yrs of development experience with ETL tools (Informatica, Azure Data Factory, etc)

· years of development experience with Python scripting experience

· years of hands-on development experience with Relational DBs (MS SQL Server, PostgreSQL, Oracle, etc.); experience with complex stored procedures and functions using SQL

·      Strong knowledge and experience in OLAP data modeling & design

·      Demonstrated expertise in performance tuning in various DB environments with large volumes of data.

·      Experience building and scaling distributed, high available systems in cloud env (Azure / AWS)

• Expertise in understanding complex business needs, analyzing, designing, and developing solutions.
• Communication and professional skills and the ability to navigate relationships across business units.

Pluses:

• Financial technology domain knowledge
• Knowledge of NoSQL DBs (MongoDB / Cassandra / Azure Cosmos DB or similar)
• Microsoft Azure Data Engineer/services related experience (ADF, Databricks, CosmosDB, Azure SQL, etc)