Data Platform Architect (Databricks)

Coastal•Indianapolis, IN

14h•Hybrid

About The Position

We are seeking an experienced, hands-on Data Platform Architect & Integration Lead to design, build, and deliver integrations that consume Master Data products published in Databricks and feed them into an enterprise commercial CRM platform, as part of a large-scale CRM modernization program. Master Data sources (customer, account, and product master) are exposed as governed data products in Databricks – curated Delta tables registered in Unity Catalog. This role owns the consumption of those data products and their reliable, validated delivery into the target CRM and enterprise ecosystem, while re-platforming existing integrations onto modern, cloud-native patterns. This is a working, hands-on leadership role. The person leads the integration workstream and personally performs the coding, code review, and deployment work – not oversight alone. Every skill listed is expected to be backed by direct, hands-on delivery experience.

Requirements

Databricks – hands-on with Delta Lake, Unity Catalog, and consuming / publishing data products; lakehouse / medallion architecture.
AI – hands-on experience applying AI in a data, integration, or software-development context.
Data services on AWS – hands-on experience building data and transformation services / pipelines on AWS.
API – hands-on REST API design, build, and implementation at scale.
PySpark – strong, hands-on PySpark and Spark SQL for data movement and transformation.
Master Data / MDM – hands-on experience integrating customer, account, and product master data into downstream systems, including schema mapping, reconciliation, and master-data change handling.
Demonstrated ability to lead a build team while remaining hands-on – doing the build, review, and deployment work directly.

Nice To Haves

Salesforce ecosystem
Snowflake ecosystem

Responsibilities

Personally perform coding, code review, and deployment activities, and any other assigned work related to this transformation – leading the team does not replace individual hands-on contribution.
Must have hands-on experience across all required skills; the person is expected to build, not only direct others who build.
Own the end-to-end integration lifecycle: design specification, build, unit testing, deployment across dev / sandbox / UAT / prod, runbooks, and knowledge transfer.
Produce design specifications, deployment steps, and rollback approaches, and deliver them hands-on.
Consume Databricks data products (Delta Lake tables via Unity Catalog) as the source of master data, respecting the data-product contract – schema, refresh cadence, quality guarantees, and access model.
Move master data from Databricks into the CRM using the appropriate pattern – Apache Iceberg interoperability, Spark / PySpark-based movement, or API-based delivery – selecting the right mechanism per integration by volume, latency, and directionality.
Build transformation and mapping logic (PySpark / Spark SQL) to reconcile the data-product schema with the target CRM data model, including handling master-data change (deltas, data-change requests, reference data).
Re-platform existing master-data integrations onto the Databricks-data-product and modern integration patterns, ensuring parity, reconciliation, and no data loss during transition.
Implement observability, data-quality checks, error handling, data-gap detection, and reprocessing across the Databricks-to-CRM flows.
Participate in and lead all relevant client meetings – design reviews, working sessions, governance forums, and status discussions – representing the integration workstream directly with the client.
Communicate technical decisions, risks, and dependencies clearly to client stakeholders and delivery teams.
Collaborate with the second System Integrator (SI) partner responsible for independently testing and validating this team’s build.
Review the second SI’s test findings, triage them, and resolve the defects – ensuring fast, clean cross-vendor root-cause and closure rather than back-and-forth.
Maintain clean build-to-test handoffs and shared traceability so defects are resolved efficiently across vendors.
Define reusable integration patterns and interface contracts for master-data flows that other build and assurance teams can work to.
Partner with data-product owners and data-engineering teams to align on data-product schemas, versioning, refresh frequency, access, and change management.
Ensure data integrity, security, privacy, and, where applicable, regulated-industry compliance across connected systems.

Benefits

Flexible working hours with an emphasis on a life-work balance
Remote flexible work
Unlimited Paid Time Off (RTO)
401K with Company Match
Medical, Vision, & Dental coverage
Competitive quarterly bonus opportunities
Continuing education and certification reimbursements
Occasional in-house competitions with spot bonuses
A flexible and fun team culture
Frequent team and culture activities, virtual & in-person, including Lunch and Learns, Happy Hours, team-building events
Monthly All-Hands calls to bring the company together
Open-door leadership policy with access to mentorship and guidance
Opportunities for accelerated growth, networking, and career guidance and support
Trust, transparency and respect across all levels of the company