• Contribute to implementing data strategies to address our clients' business challenges. • Help implement data pipelines to collect, transform, and process data in collaboration with data scientists. • Prepare presentations, demonstrations, proofs of concept (POCs), or pilot projects to showcase technological recommendations. • Develop data ingestion jobs (preparation, ingestion, processing, and quality checks). • Participate in the technical community (technology watch, knowledge sharing across Business Units, etc.).

• The Data Engineer is responsible for monitoring, expanding, and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. • Develop, test, and maintain data pipelines to support data integration and processing. • Assist in the design and implementation of data models and data warehousing solutions. • Collaborate with data scientists and analysts to understand data requirements and ensure data is accessible and reliable. • Monitor data pipelines and systems, troubleshooting issues as they arise. • Work with senior data engineers to optimize data processes and infrastructure. • Ensure data quality and integrity through regular audits and validations. • Contribute to the documentation of data processes and best practices

Lovelytics is a Databricks-focused data and AI consulting firm specializing in artificial intelligence, data, and analytics solutions. Since partnering with Databricks in 2019, Lovelytics has experienced exponential growth, growing from 50 people to over 500 over the past 3 years. Lovelytics is a trusted partner for many of the most high-profile enterprise clients in Media & Entertainment, Manufacturing, Retail & CPG, Healthcare & Life Sciences, and Financial Services. We’re looking for a Data Governance Architect to formulate data and AI governance strategies aligned with business objectives and industry best practice for our clients. You’ll define technical strategies, architect data platforms, and guide delivery teams to implement best-in-class ingestion, transformation, and storage solutions on the cloud. You’ll also partner with sales and account teams to scope engagements, shape technical proposals, and showcase Lovelytics’ Governance expertise. This role is open to remote candidates in the U.S. and Ontario, Canada. You’re also welcome in any of our offices in Arlington, VA; Chicago, IL; New York, NY; or Toronto! Primary Responsibilties: - Data and AI Governance Strategy: Formulating data and AI governance strategies aligned with business objectives and industry best practices. - Create, socialize, and implement data governance policies, procedures, and frameworks for clients while ensuring compliance. - Introduce emerging technologies and methodologies for completion of data governance tasksand capabilities. - Developed and execute data governance and/or AI Governance strategy that improved data discoverability, data quality, accessibility, usability, AI use case evaluation, and AI readiness. - Lead the successful migration of complex data architecture from on-premises to cloud environments. - Establish and enforce data governance practices resulting in improved data security and compliance. - Introduce containerization to the organization, enhancing scalability and deployment efficiency. - Mentor engineers, review architectures and code, and guide teams through implementation. - Lead technical discovery, shape solution architectures, respond to RFPs, and deliver demos and proofs of concept for data engineering engagements - Create technical blueprints and recommend tools, frameworks, and design patterns aligned to client needs Required Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. - 5+ years of experience in data governance with 4+ years in a client facing role, preferably in a professional services firm - Mastery in data governance capabilities as defined by the DAMA-DMBOK - Certified in governance toolsets such as Unity Catalog, Atlan, or Anomalo. - Expert knowledge of Databricks and Spark (required) - Experience creating proofs of concept, technical presales presentations, and pricing for engagements - Strong client-facing communication skills with the ability to influence technical and executive stakeholders - A tech stack of Google Workspace (email, tools), MacOS, Slack (internal comms), Atlassian

• Evolve engineering and data enrichment pipelines across the organization. • Optimize Python code to ensure scalability and computational efficiency. • Implement and refactor agents and processes for deployment in cloud environments (GCP). • Ensure validation and architecture of robust cloud solutions. • Collaborate across varied initiatives (hybrid profile) to support development of new products and data quality.