• Define the enterprise data architecture: Own the conceptual, logical, and physical data models for MeridianLink's analytical and operational data platform, including source-aligned, integrated, and consumption-ready layers. • Build the meta-model: Design and maintain a meta-model that captures entities, relationships, business definitions, ownership, lineage, sensitivity classifications, and SLAs — and make sure it is wired into our tooling, not stuck in a slide deck. • Drive the lakehouse strategy: Architect our medallion (bronze / silver / gold) Delta Lake patterns on Databricks; define standards for partitioning, clustering, schema evolution, slowly changing dimensions, and historical reproducibility. • Be hands-on: Write PySpark, SQL, and Delta Lake code. Build reference implementations, prototype patterns, review pull requests, and personally model critical domains rather than delegating every detail. • Lead data integration design: Set patterns for ingestion through Informatica Data Management Cloud (IDMC) and direct Databricks pipelines, including CDC, batch, streaming, and API-based sourcing from our SaaS products and third-party systems. • Champion data governance and lineage: Partner with data governance, security, and compliance leaders to operationalize cataloging, lineage, classification, masking, and access controls across the platform (Unity Catalog, IDMC, and adjacent tools). • Standardize data modeling practices: Establish the standards, naming conventions, and review processes used by the Data Engineering team. Coach engineers on dimensional modeling, Data Vault, and other techniques where they best fit the use case. • Partner across the business: Work closely with Product, Engineering, Analytics, ML, Finance, Risk, and Customer-facing teams to translate business needs into durable data designs. • Influence the roadmap: Identify gaps in tooling, capability, and skill; propose investments; and drive multi-quarter initiatives that materially improve how MeridianLink uses its data.

• Stand up and operate per-client data ingestion (ODBC, API, and file sources) into the warehouse via our ELT layer • Run rigorous row-count and parity checks to verify raw landings directly against the client’s source systems • Own end-to-end pipeline operations across concurrent clients, directly diagnosing freshness issues, failure alerts, infrastructure costs, and incidents • Build and maintain isolated, three-layer dbt projects (staging → intermediate → marts) for each client assignment • Construct robust fact and baseline models that reproduce a client’s exact source-of-truth numbers, producing reconciliation documentation for client sign-off • Perform engineering standards rigor by applying version-controlled, tested, peer-reviewed, and reproducible data practices utilizing a disciplined local-to-CI workflow • Apply right-size engineering rigor appropriately for a startup environment, partnering cleanly with platform engineering without gold-plating solutions • Sit directly with client operators, controllers, and analysts to pull essential domain logic and uncover system patterns • Translate discovery conversations directly into clear metric definitions within the semantic layer and queryable business marts • Own core business-rule tests and metric definitions (Cube.dev) powering executive dashboards and natural-language AI querying • Construct the quality framework using automated dbt tests, anomaly checks, freshness monitoring, and PII awareness • Optimize and structure context-rich datasets with clean joins and clear descriptions so AI agents can reason correctly via the signal-mcp tool server • Ensure all ongoing data operations capture structured traces that continuously feed our cross-client intelligence layers • Collaborate and train other team members • Perform other duties as required by the role

• Develop and test automation for data aggregation and consolidation • Participate in technical decisions together with the tech lead and the team.

Role Description The Data Analytics Engineer supports the data team to drive innovation in data analytics and ensuring the reliability and scalability of our data systems. - Execute a comprehensive data strategy aligned with Digistore24’s objectives. - Support to manage the full data domain: architecture, technology choices, policies, procedures, cost monitoring, alerting, etc. - Ensure the data foundation is performant and scalable to meet business needs. - Enhance analytics capabilities and drive the development of predictive models and data visualization tools. - Communicate and align with various teams on business and technical needs. - Perform on clear goals and objectives, ensuring alignment with organizational priorities. - Ensure the accuracy, reliability, and integrity of data analytics processes and outputs. - Implement best practices for data acquisition, integration, transformation, and delivery. - Stay current with emerging technologies and trends in data engineering. - Serve as a subject matter expert on data analytics and engineering topics, providing guidance and support as needed. Qualifications - Fast learner with the ability to connect business and technical perspectives. - Utilize cloud environments (AWS, Azure, preferably GCP) to manage and process data. - Work with data warehousing solutions such as BigQuery, Redshift, and Snowflake to ensure efficient data storage and retrieval. - Comfortable working across different teams, managing multithreading, and handling ambiguity. - Employ ETL tools like dbt, SQLMesh, and GCP DataForm to transform and prepare data for analysis. - Ability to build and maintain dashboards, create interactive visualizations, and generate actionable business insights using Power BI, Tableau, Looker or similar tool. - Proficient in both project management and operational work, with the ability to delegate and coach. - Self-motivated, capable of making independent decisions, and solving problems innovatively. - Excellent verbal, written, and interpersonal communication skills. - Experienced in computer science, data science, engineering, or a related field. - Proven experience in a data analyst or data engineering role. - Fluent in both written and spoken English to communicate with our international team. - Experience in ERP migrations, tax datamarts, or procurement automation; collaborate cross-functionally to enable self-service analytics for non-technical users. - Familiarity with event tracking and product analytics tools (e.g., Amplitude, Mixpanel, GA4, Segment, Snowplow). - Experience building and analyzing funnels, cohorts, and experiments to inform product roadmap and go-to-market strategy. - Ability to balance statistical rigor with speed, clearly communicating trade-offs and uncertainty. Requirements - This position is NOT for you if you have less than 3 years of experience in relevant data positions. - View software development as only the activity of code writing. - Cannot write high quality code without a modern framework or need Windows to develop. - Casually make changes to codes without understanding their consequences. - Can’t take ownership and need to discuss every detail with your product manager or colleagues. - Do not have the ambition to continuously expand your knowledge. - Do not identify with our values. - Are looking for a B2B contract: we can NOT offer this. - Are NOT based in Europe (continent). Benefits - Play a crucial role in shaping our cutting-edge projects in a collaborative work environment. - Work in our partner's coworking spaces (max. 3 days a week) or in your home office, as long as you can guarantee uninterrupted internet access. - Regular further education. - The stability of an extremely successful German high-tech company that is funded by its successful product and not by investors. - Outcome focused teams and a culture of direct feedback. - Modern equipment: MacBook. - International, collaborative team with strong cohesion. - Spectacular team events in various European countries. - Autonomy from day one. - Work in your team on a first-name basis, without a dress code, and at eye level. - Flexible working hours from Mondays to Fridays.