Role Description You will be part of a multi-disciplinary technology team, working closely with our customers (business, software vendors, and partners). Within the team, you will be responsible for a suite of data processes and will participate in all aspects from design through to testing and implementation. You will be surrounded by data professionals that strive for excellence and data best practices to realize business value. As a Data Engineer, you will work in the data engineering team to build and maintain data pipelines to ingest data into the warehouse and support integration into other systems. You will apply your knowledge of good data engineering practices and standards, and data technologies to deliver target state design and implementation. The role is challenging, and you must be adept at problem-solving and able to respond to changing priorities and rapidly evolving requirements that may have a direct impact on services to users. This role would suit a professional who is keen to grow their career in a busy team that values cognitive diversity and diversity of lived experience. Duties & Responsibilities - Maintain, support, and monitor existing production SSIS packages and SQL Queries and Stored Procedures, CICD pipelines to ensure all data loads on the data warehouse meet data quality standards and business SLA requirements. - Build, maintain, support, and monitor Synapse data engineering pipelines on the data platform if required. - Participate and contribute to data architecture design, data modelling, gathering and analysis of data requirements; understand, document, communicate, and build appropriate solutions. - Participate, design, build, deliver, and document data-related projects with various environment-specific data analytics technologies. - Promote data engineering best practices with CICD pipelines and automation. - Collaborate and work closely with team members and contribute significantly to building a high-performing, collaborative, transparent, and result-driven data engineering team. - Support the Data Engineering Practice Team Manager with best fit-to-purpose data engineering solutions, quality engineering artifacts, and high standard documentation. - Follow Data Ethics standards to protect personal information and meet our customers’, partners’, and community’s expectations. Qualifications - 8+ years demonstrable experience in design, build, and support of data engineering pipelines in data warehousing, data ingestion, cleansing, manipulation, modelling, and reporting. - Experience in ETL using Microsoft technologies. - Strong experience in writing MS SQL server queries, stored procedures, and SSIS Packages. Experience with SSRS would be an advantage. - Experience of manipulating semi-structured data (XML, JSON). - Strong knowledge and extensive experience in working in an Agile framework with CI/CD using modern DevOps / Data Ops integrated processes with YAML pipelines. - Bachelor’s degree in computer/data science technical or related field is a must. Post-graduate is highly regarded. - Knowledge of Azure Synapse data engineering pipelines, PySpark notebooks, data platform lake house architecture, and Azure SQL ODS storage is desirable.

• Develop well-scoped features, with support from Senior and Staff Engineers, for how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph, meeting team goals for data freshness, sync reliability, and graph coverage. • Build parts of integrations with external systems for business context, including Jira, observability tools, Zendesk, and ServiceNow, increasing indexed business context while meeting team goals for data completeness and freshness in the graph. • Build features for the Software Engineering Intelligence dashboards, including DORA, value stream reporting, GitLab Duo, and software development lifecycle metrics rolled up across organizational structures, meeting team goals for reporting accuracy, performance, and coverage. • Contribute to design discussions and technical direction for your features, with guidance from Senior and Staff Engineers, helping deliver secure, reliable, and performant solutions on schedule. • Raise blockers and risks early, and work with Senior Engineers to unblock your work so milestones stay on track and delivery risk is reduced. • Participate in design review and code review, and apply feedback to improve code quality, maintainability, and delivery velocity. • Build a deep understanding of the system, including the data model and the platform the team builds on, so you can ship changes more independently and resolve issues faster.

Role Description We are looking for a Corporate Data Architect who will help organize and standardize how the organization understands and uses data. Your main task will be to design and develop data architecture at the level of the entire organization so that data is consistent, well defined, and ready to be used in analytics, AI, and system integrations. You will act as a bridge between the worlds of business, data, and technology, connecting strategy, standards, and practice. - Design semantic, logical, and conceptual data models based on business domains and organizational processes. - Define and standardize the corporate data model as part of the Data Governance initiative. - Create and maintain reference architecture (logical and technical reference architectures) and design patterns for data domains. - Co-create the strategy and roadmap for data architecture development that supports the vision of the Data Governance program and organizational goals. - Collaborate with Data Governance, Data Management, Analytics, AI, and Data Engineering teams to integrate models with the data catalog and metadata management tools. - Support technical teams in implementing models in data layers. - Participate in designing data integration, flow, and quality processes (data lineage, data contracts, data quality). - Identify and certify authoritative data sources within organizational domains. - Monitor the compliance of data solutions with Data Governance policies and standards as well as architectural recommendations. - Support the resolution of data conflicts and issues. - Create architectural documentation, metamodels, and inter-domain relationship diagrams. - Consult on and develop good practices in the area of modeling, metadata, and information architecture. - Collaborate on defining the vision, priorities, and directions for the development of data architecture in the organization. Qualifications - Experience in data modeling (conceptual, logical, physical), preferably in a large organization or within complex data ecosystems. - Practical knowledge of tools and methodologies such as ER, UML, IDEF1X, Data Vault, 3NF, Kimball/Inmon. - Ability to work with data catalogs and metadata management tools (e.g. DataHub, Collibra, Alation, Atlan). - Knowledge of SQL and relational data models. - Experience working with database systems and data architecture in a cloud environment (AWS). - Ability to work with engineering and analytics teams to translate business needs into data models. - Understanding of data security, availability, and control principles. - Good command of English (reading documentation, community discussions). Requirements - Experience in Data Governance, Data Quality, Master Data, and Metadata Management projects. - Knowledge of concepts and technologies related to the semantic data layer: ontologies, RDF, OWL, GraphQL, dbt Semantic Layer, Semantic Kernel. - Knowledge of Python for automation, model validation, and API integrations. - Knowledge of event-driven data architecture. - Experience in creating and maintaining architectural documentation. Benefits - Flexible employment and remote work. - International projects with leading global clients. - International business trips. - Non-corporate atmosphere. - Language classes. - Internal & external training. - Private healthcare and insurance. - Multisport card. - Well-being initiatives.

Title: Staff Data Engineer Location: Denver, Colorado, United States; San Francisco, California, United States Job Description: About Checkr Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, Amazon, and Anthropic. We're a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company. As a Staff Data Engineer on the People Data team, you''ll help build and evolve the centralized platform that powers every Checkr product. This platform stores and serves the identity and people records that underpin Checkr''s Workforce, Mortgage, Tenant, Trust, and Personal products, making it foundational to the company''s AI-powered verification platform and every high-stakes decision our customers make. In this role, you''ll own the core services, data pipelines, and architecture that keep this platform scalable, reliable, and ready for the next generation of Checkr products. You''ll solve complex distributed systems and data engineering challenges while influencing the technical direction of one of the company''s most critical platforms. What you''ll do - Architect, design, lead, and build an end-to-end, performant, reliable, scalable data platform. - Work as an independent contributor: solve problems and deliver high-quality solutions with minimal oversight and strong ownership. - Mentor and guide junior engineers to deliver complex, next-generation features. - Bring a customer-centric, product-oriented mindset. Collaborate with customers and internal stakeholders to resolve product ambiguities and ship features that solve real customer problems. - Partner with engineering, product, design, and other stakeholders to design and architect new features. - Experimentation mindset: autonomy and empowerment to validate a customer need, get team buy-in, and ship a rapid MVP. - Quality mindset: you treat quality as a non-negotiable part of your software deliverables. - Analytical mindset: instrument and deploy new product experiments with a data-driven approach. - Monitor, triage, and resolve production issues for the team''s services. - Create and maintain data pipelines and foundational datasets to support product and business needs. What you bring Required Experience - 10+ years designing, implementing, and delivering highly scalable, performant data platforms. - Experience building large-scale data processing pipelines using ETL/ELT, batch, and stream processing. - Expert-level proficiency in PySpark, Python, and SQL. - Expertise in data modeling, relational databases, and NoSQL data stores (e.g., MongoDB). - Experience with big data technologies such as Kafka, Spark, Iceberg, data lakes, and the AWS stack (EKS, EMR, Serverless, Glue, Athena, S3, etc.). - Knowledge of security best practices and data privacy concerns. - Strong problem-solving skills and attention to detail. Nice to have - Experience or knowledge of data processing platforms such as Databricks or Snowflake. #LI-TD1 Pay Transparency Disclosure We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website. On-target Earnings OR Base Salary range (San Francisco, CA) $196,000-$230,000 USD On-target Earnings OR Base Salary range (Denver, CO) $166,000-$195,000 USD What We Offer - A fast-paced and collaborative environment - Learning and development allowance - Competitive cash and equity compensation, and opportunity for advancement - 100% medical, dental, and vision coverage - Up to $25K reimbursement for fertility, adoption, and parental planning services - Flexible PTO policy - Monthly wellness stipend At Checkr, we believe an in office work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO; San Francisco, CA; Nashville, TN; and Santiago, Chile. Individuals are expected to work from the office 3+ days a week. In-office perks are provided, such as lunch five times a week, a commuter stipend, and an abundance of snacks and beverages. A Equal Employment Opportunities at Checkr Checkr is committed to building the best product and company, which requires hiring talented and qualified individuals with a diverse set of perspectives and lived experiences. Checkr believes in hiring people of all backgrounds, including those whose histories are impacted by the justice system in accordance with local, state, and/or federal laws, including the San Francisco's Fair Chance Ordinance.