Senior Data Engineer – Data Analytics & BI

Accountabilities: Triage requests for people data, reporting, and ad hoc analysis, prioritize work, and communicate realistic delivery expectations to stakeholders. Design, develop, automate, and maintain scalable ETL/ELT pipelines that ingest, transform, validate, and deliver data from diverse internal and external sources. Build self-service reports, dashboards, and data visualizations that communicate meaningful KPIs and enable leaders to identify insights and make informed decisions. Partner with stakeholders to define reporting requirements and continuously improve core dashboards, analytics solutions, and data products. Use SQL, Python, Tableau, Jupyter Notebook, and related technologies to extract, organize, analyze, and visualize data from multiple sources. Collaborate with Data Engineering, Data Science, and other cross-functional teams to apply effective practices in data collection, pipeline architecture, analytics, and solution development. Audit data integrity, investigate data-quality issues, and establish processes that improve the accuracy, consistency, and reliability of reporting and analytics. Optimize ETL processes through effective architecture, code optimization, and performance improvements. Provide guidance and coaching to end users on interpreting metrics, using dashboards, and applying data effectively. Document reporting requirements, technical designs, data definitions, operational procedures, and changes to analytics solutions. Participate in on-call responsibilities, monitoring data systems and responding to operational issues to maintain reliability and uptime. Stay current with emerging data engineering practices, analytics technologies, cloud platforms, and industry trends. Requirements: 8+ years of professional experience with SQL, including complex query optimization and large-scale relational and columnar databases. 5+ years of hands-on Python experience focused on data engineering, including pipeline development, automation, and data transformation. 8+ years of experience developing custom reports, dashboards, and visualizations using Tableau or comparable business intelligence tools. Strong experience with data management, including validating, auditing, and reconciling data and reports across multiple systems. Hands-on experience with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform, as well as distributed technologies such as Spark or Hadoop. Strong knowledge of relational database systems and familiarity with NoSQL technologies such as MongoDB or Cassandra. Experience with data orchestration and transformation tools such as Apache Airflow and dbt. Experience with Apache Hive and Presto for large-scale distributed query processing. Experience supporting large-scale data migration initiatives, including requirements gathering, pipeline design, implementation, and operational support. Familiarity with machine learning concepts, algorithms, and data science workflows. Understanding of DevOps principles and their application to data management, deployment, and operational workflows. Experience mentoring or coaching junior engineers and analysts. Bachelor's or master's degree in computer science, mathematics, statistics, engineering, social sciences, physical sciences, or another discipline emphasizing data analysis and visualization, or equivalent professional experience. Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical audiences and collaborate effectively with stakeholders at all levels. Strong technical documentation skills, including the ability to create design specifications, runbooks, data dictionaries, and other technical materials. Comfortable working in ambiguous, fast-paced environments and shifting between strategic initiatives and tactical analytics requests. A strong commitment to engineering excellence, including thorough testing, clear documentation, maintainable solutions, and a "do it the right way" mindset. Ability to work effectively with distributed teams and communicate through remote collaboration and video-conferencing tools. Benefits: Competitive compensation, with the role advertised at approximately $135,000 . Remote work environment. Opportunities for continuous professional development and training. Access to learning opportunities and industry certifications. Collaboration with experienced data, engineering, analytics, and technology professionals. Comprehensive benefits designed to support employees' professional and personal well-being. A collaborative and inclusive work environment focused on professional growth. Opportunities to work on large-scale data, analytics, cloud, and business intelligence initiatives. A culture that emphasizes continuous learning, teamwork, inclusion, and employee development.