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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Warehouse Engineer - **Company:** Maverick Payments - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $110,000.0 - $125,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, BigQuery, Code Review, Continuous Integration, Data Dictionary, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Masking, Data Warehousing, Database Queries, Dimensional Modeling, Github, JSON, Log Analysis, PCI Data Security Standards, Performance Tuning, Query Optimization, Role-Based Access Control, Power BI, Kusto Query Language, Azure Data Lake, SQL Stored Procedures, SQL Databases, Transact-SQL, Parquet, Azure Data Factory, Sql Optimization, Cloud Monitoring, Snowflake, Change Data Capture, Indexer, Git, Data Layers, Build Management, Data Lakes, Data Lineage, Bicep, Api Design, Terraform, Azure Synapse Analytics, Data Pipelines, Serverless Computing, Key Vault, Amazon Redshift - **Published:** June 29, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f9912f562ebafa77 ## About the Role Do you have experience in Vendor communication?, * 3+ years in data engineering/data warehousing or related technical roles. * Advanced SQL/T-SQL: complex queries, stored procedures, views, indexing, and performance tuning. * Hands-on Azure: Data Factory, Synapse SQL, Data Lake Gen2, Key Vault (or strong equivalents: Snowflake, BigQuery, Redshift). * Proven delivery of ETL/ELT for file-based (CSV/JSON/Parquet) and API data sources. * Strong data modeling: star/snowflake, dimensional modeling, fact/dimension tables, SCDs (Type 1/2). * Git proficiency and CI/CD concepts for infra/pipeline deployment (Azure DevOps/GitHub Actions; ARM/Bicep/Terraform a plus). * Demonstrated troubleshooting and RCA across complex systems; able to drive solutions independently. * Experience supporting BI/analytics consumers (Power BI preferred; semantic models, incremental refresh, gateway basics) * Advanced SQL/T-SQL; performance tuning; query optimization; indexing; statistics; partitioning; workload management * Azure Data Factory; pipeline orchestration; triggers; parameterized reusable templates; error handling; retries; idempotency * Azure Synapse (dedicated/serverless SQL pools); PolyBase/COPY INTO; distribution strategies (hash/round-robin/replicate) * Azure Data Lake Gen2; Parquet/Delta; hierarchical folder structures; retention/archival; lifecycle management * Incremental loads; CDC; SCD Type 2; watermarking; late-arriving data; schema evolution * Data modeling (Kimball); dimensional schemas; semantic layers; Power BI model optimization * Observability & reliability: Azure Monitor, Log Analytics, KQL, alerts, dashboards; SLA/SLO adherence, post-mortems * Security & governance: RBAC/ACLs, Key Vault, Managed Identity, Private Endpoints/Virtual Networks, data masking, tokenization, Purview lineage/catalog * DevOps: Git, pull requests, code reviews; CI/CD (Azure DevOps/GitHub Actions); IaC (ARM/Bicep/Terraform) * Cross-functional communication; clear documentation; vendor collaboration; prioritization by business impact; ownership mindset ## Description The Data Warehouse Engineer is a hands-on role responsible for designing, building, and operating Maverick's Azure data platform. Reporting to the Data Team Director, you will partner with external implementation resources in Phase 1 and then own daily operations, reliability, and continuous improvement of the platform. The role balances operational excellence (pipeline uptime, SLAs, observability) with platform development (new data pipelines, sponsor bank integrations, performance/cost optimization). Your work enables the Maverick organization to access reliable, timely, and governed data for analytics, BI, and regulatory reporting. * Monitor health and SLAs via Azure Monitor/Log Analytics, Synapse and Data Factory dashboards; respond to critical pipeline incidents within 2 hours. * Triage and resolve data integration failures (sponsor bank files, CRM/ITSM connectors, API ingestions), distinguishing data quality vs. pipeline vs. infrastructure issues; escalate when needed. * Perform root-cause analysis (RCA) and drive corrective actions; maintain and conduct post-mortems. * Support users with ad-hoc SQL, Power BI connectivity, refresh scheduling, and semantic model best practices. * Track pipeline performance and data freshness, optimize query runtimes, memory, and SLA compliance. * Design and build Azure Data Factory pipelines (ETL/ELT) for batch and incremental ingestion using parameterized, reusable templates. * Write and optimize T-SQL in Synapse SQL pools for reliability and maintainability. * Implement incremental loads, CDC (Change Data Capture), idempotent retries, and robust error handling. * Onboard new sponsor banks and data sources against the Director's roadmap; standardize patterns for file-based (CSV/JSON/Parquet/Delta) and API-based data. * Strengthen data quality and observability with validation checks, reconciliations, and anomaly detection * Optimize Synapse cost and performance: distribution strategies (hash/round-robin/replicated), partitioning, indexing and statistics, workload management, scale up/down and pause/resume patterns, and archival/retention strategies. * Collaborate with vendors during Phase 1; participate in code reviews, document architecture decisions (ADRs) and platform standards. * Integrate Microsoft Purview for data lineage/catalog for transformation governance where appropriate. * Create and maintain runbooks ("respond to X failure"), troubleshooting guides, and common query patterns. * Document pipeline architecture, data lineage, schemas, and transformation logic for knowledge transfer. * Maintain a data dictionary/metadata (descriptions, refresh cadence, PII tags, sensitivity labels). * Train internal stakeholders on basic SQL and data request procedures; contribute to architecture diagrams. * Assist with PCI-DSS and SOC 2 reviews (encryption at rest/in transit, RBAC/ACLs, Key Vault, Private Link, Managed Identity, least privilege). * Stay current on Azure/Synapse best practices, security updates, and cost optimization. * Attend vendor training in Phase 1; pursue DP-203, DP-300 (preferred). * Share knowledge with the Director and future data science hires via code examples, patterns, and mentoring. * Deliver specialized data engineering enhancements as directed by the Data Team Director. * Support ad-hoc analysis, process improvements, and cross-functional analytics. * Evaluate emerging Azure services and tooling for platform improvement. * Other duties as assigned., Notice to Agency and Search Firm Representatives: Maverick Payments is not accepting unsolicited resumes from agencies and/or search firms for this or other job postings. Resumes submitted to any Maverick Payments employee by a third-party agency and/or search firm without a valid written and signed search agreement, will become the sole property of Maverick Payments. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. ## Related Videos - [Back(end) to the Future: Embracing the continuous Evolution of Infrastructure and Code](https://www.wearedevelopers.com/videos/440-back-end-to-the-future-embracing-the-continuous-evolution-of-infrastructure-and-code) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Introducing JSON Structure](https://www.wearedevelopers.com/videos/100219-introducing-json-structure) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)