Technical Program Manager, Data Lake

Ansira•Northampton, MA

17h

About The Position

Ansira is consolidating and scaling a unified, enterprise Data Lake to integrate product, media, and business data, standardize reporting, and accelerate decision-making across the organization. We are seeking a Technical Program Manager (TPM) to lead this cross-functional program end-to-end — aligning product and engineering roadmaps, driving ingestion and migration from legacy systems, maturing data governance and quality, and ensuring business adoption of standardized, self-serve analytics. This leader will orchestrate work across Ansira’s Product solutions, Data Engineering, Data Science/BI, Media, and Client Partnership teams, with a clear mandate: deliver consistent, governed, and performant data to downstream products and reporting while deprecating redundant systems and minimizing operational cost.

Requirements

8+ years in Program/Project/Product Management, with 5+ years leading complex data platform initiatives in a cloud environment.
Proven delivery of cross-functional data programs involving multiple product lines and business stakeholders; strong executive communication.
Hands-on experience with modern data stacks: one or more of Snowflake/BigQuery/Databricks; Azure Data Factory/Airflow; dbt; Kafka/Kinesis; Git/Terraform; REST/SFTP integrations.
Strong grounding in data governance and quality practices, data contracts, catalog/lineage, and secure data access.
Demonstrated expertise in Agile at scale (Scrum/Kanban), Jira/Confluence, dependency/risk management, and budget tracking (including CAPEX/OPEX).
Competent SQL skills for validation/triage; fluency in reading pipeline/log artifacts and interpreting BI/semantic model requirements.

Nice To Haves

Background in marketing/media data and standardized performance reporting (e.g., Media (AdTech/LBN), campaign hierarchies, Power BI embedded).
Prior experience migrating from legacy ETL/BI ecosystems (e.g., Alteryx/Insighter/Tableau) to a lakehouse with standardized semantic layers.
Experience establishing data domains and productizing data (SLAs, contracts, versioning, lifecycle) to accelerate downstream analytics.
Familiarity with privacy, security, and compliance standards (e.g., RBAC/ABAC, PII governance) and enterprise SSO/permissions models for embedded analytics.
FinOps mindset: cost observability, unit economics, and right-sizing compute/storage.

Responsibilities

Own the multi-quarter program plan for the unified Data Lake: scope, roadmap, milestones, budgets (OPEX/CAPEX), risks, and dependencies.
Stand up and run the operating model: weekly workstream standups, cross-functional syncs, monthly steering committee, and a transparent executive status rhythm.
Build and maintain a single-source-of-truth for delivery: program charter, RACI, RAID log, decision log, intake/triage process, and dashboards for progress/risks.
Drive the migration plan from legacy pipelines and tools (e.g., Alteryx, Insighter) to the target stack (e.g., Snowflake, Power BI embedded via platform connectors).
Coordinate parallel workstreams (ingestion, modeling, governance, reporting cutover) to hit time-bound deliverables with predictable quality.
Define and maintain the Data Lake program backlog, translating business use cases into technical epics, data contracts, and acceptance criteria.
Partner with Product and Data Science teams to standardize media and product reporting packages and ensure they’re backed by governed, contract-driven data.
Prioritize sources and domains for ingestion based on business value, client impact, and technical feasibility; establish clear go/no-go gates.
Align with platform architecture to ensure scalable patterns for batch/stream ELT/CDC, cost control, observability, and reusability across domains.
Establish practical data contracts with upstream product and business owners; define schema, SLAs, lineage, and DQ checks at ingestion.
Stand up governance ceremonies and roles (data owners, stewards) and implement data catalog/lineage practices to improve discoverability and trust.
Define and monitor quality KPIs (completeness, timeliness, accuracy) and drive remediation plans with accountable teams.
Ensure data privacy, compliance, and security best practices (e.g., PII handling, role-based access, data masking) across environments.
Serve as the connective tissue across Product, Engineering, Data Science, Media, Finance, and Client Partnership — communicating decisions, trade-offs, and timelines.
Lead change management for reporting standardization (e.g., Media (AdTech/LBN)-based standard reports), business onboarding to the lake, and client-facing cutovers.
Create enablement assets (runbooks, playbooks, onboarding guides) and training plans to accelerate adoption and reduce support burden.
Partner effectively with architects and data engineers on Snowflake/BigQuery/Databricks, Azure/AWS/GCP services, orchestration (ADF/Airflow), and transformation (dbt).
Understand ELT/CDC patterns, API/file ingestion, schema design for analytics, and BI tooling (Power BI, Looker).
Write and review basic SQL for validation.
Apply FinOps and performance/cost optimization practices (storage tiers, compute sizing, job scheduling, caching strategies).