• As a Senior Data Engineer at Coody, you'll dive into technically exciting and intellectually challenging assignments to design and build fully automated data platforms and pipelines that creates real business value. • Each assignment is 6–24 months and will give you both broadness and deepness from various industries and companies. • As a consultant, you are expected to ramp up fast and deliver value from day one, often in new environments.

• Meet with clients to understand their current business processes and needs to provide consulting services and direction on how to build or grow their current data strategy. • Work with HBS Sales Solutions consultants to identify and grow opportunities within HBS client environments. • Support and administer the underlining infrastructure and layout of a client data environment. • Develop and design the process for the customer data collection process. • Develop policies and procedures for the collection and analysis of data. • Review customer sources to ensure integrity of the data collection process. • Collaborate with the BI Data Developers to ensure the requirements are being met to build the right solution needed. • Estimate development effort required to deliver data customer needs and requests. • Use business analysis skillset to identify development needs for the purpose of streamlining and improving the operations of the organization for efficiency and profitability. • Ability to work independently or as a team on project-based solutions for clients. • Work with team mates to continue to grow and mature data services and delivery options for HBS clients. • Based on experience, one may mentor other engineers in developing scalable, secure, high-performance BI and Data solutions. • Meet annual billable hour goal, as defined by HBS. This number may change over time as the business evolves.

• Develop data models that support exploratory analyses, dashboards, and predictive models; • Collaborate with Business and Data Science teams to structure analytical datasets (Data Marts, Views, Semantic Layers); • Design and optimize SQL queries for analyses on high-volume data; • Document applied business rules; • Explore data to identify patterns, anomalies, and opportunities for process improvement; • Implement data governance and data quality best practices (lineage, catalog, consistency); • Support product, marketing, and business teams in understanding the data and enabling ad-hoc analyses.

Role Description This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Engineer - REMOTE. You will play a crucial role in shaping the backbone of the data platform, ensuring security, reliability, and trust while managing vast volumes of data from workouts and health-related sources. Your expertise will directly impact product innovation, AI, and analytics, allowing our partner to continue redefining the training experience. By building and scaling data systems, you'll contribute to personalizing experiences and enhancing coaching. Your work will ensure that sensitive information is protected while maintaining compliance with an ever-evolving regulatory landscape. - Architect secure and scalable data systems that support growth and meet regulatory standards. - Build and optimize data models and pipelines across diverse sources: sensors, workouts, and health integrations. - Establish controls for access, encryption, anonymization, monitoring, and auditability. - Define and enforce best practices for managing sensitive data, including PHI and PII. - Collaborate with teams across various departments to translate needs into compliant solutions. - Conduct risk assessments and implement safeguards guided by NIST frameworks. - Support SOC 2 audits by documenting and demonstrating effective security controls. - Mentor engineers and scientists, setting high standards for secure data engineering. - Continuously evolve the platform, introducing tools and frameworks to balance innovation with regulatory compliance. Qualifications - 8+ years of experience in data engineering, or 6+ years with a Master’s degree (or equivalent). - Strong skills in SQL, Python, and distributed data processing (Spark, Databricks, or similar). - Experience building pipelines with DBT, Airflow, Fivetran, or related tools. - Background in data modeling and warehousing with systems like Snowflake, Databricks, or Redshift. - Hands-on experience working with regulated environments and sensitive data. - Familiarity with frameworks such as HIPAA, SOC 2, and NIST for security and compliance. - Skilled in access control design, audit logging, encryption, and governance. - Excellent communicator who can explain complex tradeoffs to both technical and non-technical audiences. - Known for technical leadership and mentoring, raising the bar for engineering quality. Benefits - Flexible work schedule with remote opportunities. - Collaborative work environment with cross-functional teams. - Opportunities for professional growth and development. - Inclusive culture that celebrates diversity and nurtures unique perspectives. - Support for accessible work arrangements and accommodations. - Innovative projects that leverage cutting-edge technology and data. - Participation in ongoing training and skill enhancement programs.