Data Warehouse Engineer

Role 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 with platform development.

• 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, 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.

Qualifications

• 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.

Benefits

• Competitive Salary, Bonuses and Incentives.
• Comprehensive employer sponsored health, vision, and dental insurance programs.
• Paid time off, Paid Sick and Paid Holidays.
• 401K plan with up to a 3% matching contribution.
• Commitment to Career Development and Advancement.
• Vibrant Office Culture, Team Building, Birthdays, Work Anniversaries, Snacks, and more!

Pay Range

$110K-125K

Company Description

Maverick Payments is a family-owned and privately held full-service payment provider. Located in Calabasas, California, Maverick has created innovative technology designed for sales organizations, such as ISO’s and ISV’s, looking to monetize payments by reselling our white-labeled payments stack.