• Partner with Enterprise Architects, Senior Architects, and cross functional teams • Contribute to Empower’s technology roadmap • Design and support modernization and migration of complex systems • Evaluate and prototype new technologies • Apply and help operationalize architectural standards • Collaborate closely with business and engineering teams • Provide architectural guidance in process design • Champion security, resilience, and scalability as core design principles • Contribute to architecture discipline maturity • Support full stack development teams through solution design

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role is a key member of the Enterprise Data Warehouse team, responsible for designing, developing, and optimizing data solutions that support business and client needs. The Senior Data Warehouse Engineer will lead the creation of scalable ETL/ELT pipelines, manage complex data integration projects, and ensure adherence to data governance standards. - Design, develop, test, deploy, and maintain complex ETL/ELT processes to integrate diverse data sources. - Optimize SQL queries, database structures, and data pipelines for performance and scalability. - Ensure compliance with data privacy, governance, and organizational standards across all data processes. - Collaborate with cross-functional project teams to understand business requirements and deliver actionable data solutions. - Support technical design, project planning, and solution deployment activities. - Act as a technical subject matter expert (SME) for assigned business segments, guiding best practices in data engineering. - Identify opportunities for continuous improvement in business processes, system capabilities, and delivery methodologies. Qualifications - Bachelor’s degree in Computer Science, Information Systems, or related field. - 5+ years experience with relational databases and ETL development. - 5+ years experience writing and optimizing SQL queries. - 3+ years experience working with healthcare data in a Data Engineer capacity. - 2+ years experience with Snowflake, Azure Data Factory, and Azure Synapse. - 2+ years experience with SQL Server Integration Services (SSIS). - Experience building data pipelines and working with APIs for ETL processes. - Familiarity with multiple file formats (JSON, XML, etc.) and proficiency in Python, R, or SAS. - Strong problem-solving, communication, and collaboration skills for cross-functional environments. Benefits - Competitive salary and growth opportunities. - 401K plan with company match. - Tuition reimbursement programs. - Flexible work environment and telecommuting options. - Paid time off, holidays, and discretionary PTO. - Medical, dental, and vision coverage, including HSA/FSA options. - Employee wellness and assistance programs. - Short-term and long-term disability, life insurance, and adoption assistance. - Access to professional development and learning resources.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description First American Trust is seeking a Senior Data Engineer to help develop and grow our data engineering capabilities to enhance the Strategic Product Development Organization. You will help FA Trust’s Data Engineering team make real-time decisions based on the datasets, facilitate analytics on existing products, and provide insights on potential new opportunities for growth. You will partner with subject matter experts to help us solve business problems with data. You will mentor data engineers and junior data engineers by providing guidance, advice, and support in various facets of data engineering. - Build high-performing cloud data solutions to meet our analytical and BI reporting needs. - Design, build, and operate secure, scalable cloud data pipelines that support analytics and data products. - Integrate new data sources into the central data warehouse and deliver curated data to applications and other downstream destinations. - Identify, design, and implement internal process improvements, such as automating manual processes, optimizing data delivery, and re-designing infrastructure for greater scalability. - Build and enhance a shared data lake that powers decision-making and model building. - Implement data governance best practices across pipelines and datasets, including data quality checks, metadata management, lineage, and access controls. - Partner with teams across the business to understand their needs and develop end-to-end data solutions. - Collaborate with analysts to perform exploratory analysis and troubleshoot issues. - Coach and develop the team by providing hands-on mentorship to engineers, lead code and design reviews, create training/onboarding content, and run knowledge-sharing sessions. - Manage and model data using visualization tools to provide the company with a collaborative data analytics platform. - Build tools and processes to help make the correct data accessible to the right people. - Participate in active rotational support role for production during or after business hours supporting business continuity. - Engage in collaboration and decision making with other engineers. - Lead presentations regularly for stakeholders. Qualifications - 5+ years of development experience with any of the following software languages: Python and SQL with cloud experience (Azure preferred or AWS). - Hands-on data security and cloud security methodologies. Experience in configuration and management of data security to meet compliance and CISO security requirements. - Experience creating and maintaining data intensive distributed solutions (especially involving data warehouse, data lake, data analytics) in a cloud environment. - Proven experience with relational and non-relational databases (e.g., PostgreSQL, Oracle, Azure Cosmos DB, MongoDB), including schema design, indexing, query optimization, and operational management in a cloud environment. - Hands-on experience in modern Data Analytics architectures encompassing data warehouse, data lake etc. designed and engineered in a cloud environment. - Demonstrated experience applying data governance best practices, including data quality validation, cataloging/metadata, lineage, and role-based access controls. - Hands-on expertise with LLMs and generative AI workflows. Familiarity with AI governance and privacy-preserving techniques. - Proven professional working experience in Event Streaming Platforms and data pipeline orchestration tools like Apache Kafka, Fivetran, Apache Airflow, or similar tools. - Proven professional working experience in any of the following: Databricks, Snowflake, BigQuery, Spark in any flavor, HIVE, Hadoop, Cloudera or RedShift. - Experience developing in a containerized local environment like Docker, Rancher, or Kubernetes preferred. - Experience with or knowledge of Agile Software Development methodologies. Requirements - Data Modeling - Design schema and data pipelines to ingest, standardize, and deliver data from various sources into the data warehouse or data lake using ETL/ELT patterns. - Create, maintain, and optimize database structures to efficiently store and retrieve large volumes of data. - Evaluate data trends and model simple to complex data solutions that meet day-to-day business demand and plan for future business and technological growth. - Implement data cleansing processes and oversee data quality to maintain accuracy. - Function as a key member of the team to drive development, delivery, and continuous improvement of the cloud-based enterprise data warehouse architecture. Benefits - Comprehensive benefits package including medical, dental, vision, 401k, PTO/paid sick leave and other great benefits like an employee stock purchase plan. Pay Range $129,300.00 - $172,300.00 Annually. This hiring range is a reasonable estimate of the base pay range for this position at the time of posting. Pay is based on a number of factors which may include job-related knowledge, skills, experience, business requirements and geographic location.

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support humanitarian operational and analytical needs. • Build and optimize data models, schemas, and cloud-based data architectures to support dashboards, machine learning workflows, and advanced analytics. • Respond quickly to database problems that arise and carry out periodic maintenance and troubleshooting. Monitor the system performance by performing regular tests, troubleshooting, and integrating new features. • Integrate heterogeneous humanitarian data sources. • Implement data quality, validation, and monitoring processes to ensure accuracy, reliability, and transparency. • Maintain an awareness of trends and developments in database maintenance. • Maintain documentation, metadata, and data governance standards in alignment with state department policies. • Occasionally, respond quickly to data needs for responses to rapid onset disasters or urgent decision-making requests. • Explore and analyze complex humanitarian datasets to identify trends, anomalies, risks, and opportunities. • Produce actionable insights that inform policy, resource allocation, program design, and crisis response. • Support predictive analytics or light machine-learning workflows where appropriate. • Communicate analytical findings clearly to technical and non-technical audiences. • Serve as a subject-matter resource for data best practices, including how to access, interpret, and apply available datasets. • Work closely with the team business analyst and HA decision makers to understand their data needs and translate them into analytical or technical solutions. • Provide training, informal guidance, and practical tools to staff who rely on data for decision-making. • Demonstrate flexibility by taking on adjacent responsibilities as needed in a small, fast moving team environment to ensure project goals are met. • As needed, may serve on temporary detail within the bureau to meet operational needs during staff shortages.