Data Engagement Lead (Analytics Engineering & Client Delivery)

Skills you’ll use every day: data engineering · analytics engineering · dbt · SQL · Snowflake / BigQuery · data warehouse implementation · client relationship management · stakeholder management · project management · consulting · data modeling · business intelligence (Omni, Looker, Tableau), * 7+ years in data engineering, analytics engineering, or data consulting, including at least 2 years as the senior-most person accountable for a client relationship - ideally at a smaller shop or team where there was no one more senior to catch mistakes or step in. \n

• Fluency across the modern data stack: SQL and dbt at an expert level; hands-on with Snowflake and/or BigQuery; experience with ingestion tools (Fivetran, Airbyte, dlt) and orchestration (Dagster, Orchestra, Airflow, or similar); comfortable in a BI/semantic-layer tool (Omni, Looker, Tableau). Python proficiency not required, but exposure is preferred., * Nice to have: prior experience at a boutique data consultancy; exposure to PE-backed or multi-location operators; experience with AI-enabled analytics or agentic tooling in delivery; Python for pipeline and automation work.

• Run engagements from Phase 0 through retainer. Lead data assessments, design the client’s data architecture, scope and price a build, drive delivery, and transition the client into ongoing support. \n

• Own the client relationship. Run the weekly syncs, set expectations, push back on scope creep, flag risks early, and give brutally honest assessments even when the answer is inconvenient. No surprises, internally or externally. \n

• Set the plan and drive it. Decide what gets done by when, prioritize across a backlog in Linear, and hold both the team and the client to it. \n

• Stay hands-on. You’ll still write dbt models, review PRs, design marts, validate numbers against source systems, and build in Omni. The bar is that a client’s finance team can rely on what you ship. \n

• Develop the team. Mentor employees, review their work, and create the “at bats” that let them grow into leading workstreams themselves. \n

• Contribute to how we deliver. Help mature our playbooks, accelerators, and engineering standards so the next engagement starts from a proven framework rather than from scratch. \n

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About South Shore Analytics

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South Shore Analytics builds and maintains modern data infrastructure and AI enablement for multi-location and growth-focused companies, with the hands-on quality and business understanding of a partner, not a vendor.

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Founded in 2022, we’re a small team of senior practitioners delivering end-to-end data stacks for PE-backed and growth-stage businesses across healthcare, restaurants, car washes, manufacturing, pet services, sports and recreation, and more. Our clients typically have 10 to 100 locations, fragmented systems that don’t talk to each other, and a board that wants reliable reporting that often doesn’t exist yet.

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We fix that by implementing some or all of the following for our clients: orchestrated data ingestion, a cloud-based data warehouse, a thoughtfully designed dbt project, a semantic layer, BI (primarily Omni), AI enablement, and ongoing managed support.