Data Architect
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About the role
As Data Architect , you won't just build pipelines; you will be the architect of our data evolution. You will contribute to the vision for our analytics and reporting platform, ensuring it is scalable, resilient, and - most importantly - an accelerator for the entire organization. Our data platform powers customer-facing embedded analytics that thousands of users rely on daily. You will be building the foundation that enables our customers to make data-driven decisions about their revenue effectiveness programs. You will participate in the design of our Medallion architecture, star schemas, and data governance frameworks. Your goal is to build a platform so robust and intuitive that other teams are empowered to build their own "Gold" tier models with speed and autonomy.
Responsibilities
- Architectural Stewardship: Contribute to the long-term vision of our data lake, entity-relationship models, and data catalog (Glue/Lake Formation). You will serve as a Data Architect for our Medallion architecture and star schemas.
- Embedded Analytics Leadership: Solve the unique challenges of customer-facing data: ensuring multi-tenant data isolation, achieving sub-second query latency, and maintaining strict SLAs for our white-labeled analytics products.
- Team Enablement: Act as a primary enabler for cross-functional teams, providing the tooling, standards, and mentorship they need to build high-quality downstream data models.
- Data Governance & Quality: Establish the "rules of the road" for data contracts, schema evolution, and lineage to ensure our data remains a trusted source of truth.
- Strategic Collaboration: Partner with Product and Engineering leadership to translate complex business needs into cost-efficient, pragmatic technical roadmaps.
- System Evolution: Lead the transition toward modern table formats (Apache Iceberg) and high-performance analytics engines (Clickhouse/OpenSearch).
- Our Tech Stack
- We are deep in the AWS ecosystem , emphasizing performance and cost-efficiency:
- Orchestration & Transformation: dbt, Glue Jobs, AWS ECS Fargate.
- Storage & Catalog: S3 Datalake (Iceberg/Hive), Glue Data Catalog, Lake Formation.
- Compute & APIs: AWS Lambda (TypeScript/Python), Athena.
- Analytics & BI: Clickhouse, OpenSearch, AWS QuickSight, Luzmo (or experience with similar BI/embedded analytics tools).
- Infrastructure: CDK / CloudFormation.
Requirements
- The "Architect" Mentality: You don't just solve the immediate problem; you build systems that prevent future ones. You prioritize pragmatic, cost-efficient solutions over "shiny object" syndrome.
- Mastery of Data Modeling: Expert-level knowledge of Kimball star-schema and dimensional modeling. You know when to follow the rules and when to break them.
- Large-Scale Experience: Proven track record of managing large-scale, event-driven systems and complex ingestion workflows.
- DevOps Mindset: You believe in CI/CD, automated monitoring, and "DataOps" as a standard, not an afterthought.
- Communication: The ability to explain complex architectural trade-offs to non-technical stakeholders.
- Company Highlights:
- Welcome to the new era of revenue effectiveness. The merger of Showpad and Bigtincan is creating the first AI-powered platform to strengthen the entire field selling motion.
- Acclaimed by analysts and adored by customers, we're recognized as a Leader in the Forrester Wave™ Revenue Enablement Platforms, honored by Gartner as a Customers' Choice in Revenue Enablement Platforms, and, together, endorsed by nearly 3,000 5-star customer reviews on G2.
- United, we're focused on powering the next generation of field selling success through a more holistic engine that creates lasting value for our customers and a new vision for our category.
- Discover the revenue team outcomes we're driving together at showpad.com .
- What you can expect from Showpad
- We are committed to creating a diverse and inc
Benefits
Additional Information
Location Qualifications: This role is available for hybrid work (2 days on-site) from our office in Bucharest.
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