Senior Data Engineer

WatchGuard Technologies • Miami, FL

13d • $140,000 - $150,000 • Hybrid

About The Position

We are looking for a Senior Data Engineer to join our growing data platform team. You will own the design, build, and reliability of our cloud-native data lakehouse — from raw ingestion through to analytics-ready Gold tables. You will work closely with data analysts, analytics engineers, and product stakeholders to deliver trusted data at speed, while championing data quality and observability as first-class concerns. This role sits at the intersection of data engineering and platform engineering — you will be expected to think in architectures, not just pipelines.

Requirements

• Snowflake: Snowflake – Advanced SQL — window functions, CTEs, recursive queries, query profiling – Snowflake-native features: streams, tasks, snowpipe, dynamic tables, row-level security – Virtual warehouse tuning and credit cost optimisation
• dbt + Elementary: dbt + Elementary – Writing, testing, and documenting production dbt models – Elementary integration for data observability and anomaly detection – dbt incremental strategies, snapshots, and semantic layer
• Azure Cloud: Azure Cloud – Azure Data Factory — pipeline authoring, triggers, parameterisation, linked services – ADLS Gen2 — zone/folder design, lifecycle management, Parquet/Delta partitioning – Azure Key Vault — secret management, managed identities – Azure Functions / Logic Apps — event-driven triggers and lightweight automation
• Airflow: Airflow – DAG authoring, task dependencies, XCom, sensors, and connection management – Airflow deployment and monitoring in cloud-hosted environments
• Python: Python – Data pipeline scripting, PySpark basics, REST API integration – Unit testing pipeline logic and transformation functions
• Data Quality & Medallion Architecture: Medallion Architecture: – Hands-on experience implementing Bronze / Silver / Gold Medallion architecture – Data validation checks at each layer — not just at the final Gold layer – Schema evolution handling and SCD Type 2 dimension management
• 4+ years of professional data engineering experience with at least 2 years on Azure cloud data platforms.

Nice To Haves

• Exposure to Snowflake Cortex, dbt Semantic Layer, or Boomi Data Hub for AI-assisted data enrichment within pipeline layers.
• Experience integrating LLM-based quality checks or AI-assisted anomaly detection into data workflows.
• Familiarity with Microsoft Fabric and OneLake as a complementary or future-state platform.
• Knowledge of data mesh or data product thinking and how it maps to Medallion layer ownership.
• Experience with Terraform or Bicep for Azure infrastructure provisioning.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory (ADF) and Apache Airflow, processing structured and semi-structured data across the Medallion architecture (Bronze → Silver → Gold).
• Implement incremental load patterns, change data capture (CDC), and event-driven ingestion to ensure data freshness across the platform.
• Build and optimise Snowflake data warehouse objects — tables, views, dynamic tables, streams, tasks, and stored procedures — for performance and cost efficiency.
• Develop modular, tested dbt models aligned to each Medallion layer, enforcing consistent naming conventions, documentation, and lineage across all transformations.
• Embed automated data validation at every Medallion layer using Elementary (dbt's observability layer), ensuring anomaly detection, freshness checks, and schema drift alerts are in place before data reaches consumers.
• Define and enforce data contracts between producers and consumers — row count checks, null rate thresholds, referential integrity, and value domain validation.
• Build and maintain data quality dashboards to give engineering and business stakeholders real-time confidence in platform health.
• Manage and optimise Azure Data Lake Storage Gen2 (ADLS) — folder structures, lifecycle policies, access tiers, and partition strategies.
• Build and maintain Azure Functions and Azure Logic Apps for lightweight event-driven processing, orchestration triggers, and operational automation.
• Manage secrets, credentials, and environment-specific configuration securely using Azure Key Vault — no hardcoded credentials in pipelines or code.
• Contribute to infrastructure-as-code practices for provisioning Azure data services (Terraform or Bicep preferred).
• Translate ambiguous business requirements into well-defined data models and pipeline designs, working with analysts and stakeholders to validate assumptions before build.
• Participate in code reviews, enforce standards, and mentor junior engineers on data engineering best practices.
• Support CI/CD adoption for pipeline and dbt model deployment across Dev / Test / Prod environments.

Benefits

• Comprehensive benefits plan including medical, dental, vision, disability, and life insurance
• Healthcare HSA
• HSA with employer contribution
• 10 paid holidays
• 10 days of paid annual leave
• 9 days of paid sick time
• Paid parental leave
• 401(k) with employer match
• Education assistance program
• Dependent Care HSA match
• Adoption assistance
• Fertility care support
• Backup care for family and pets
• A growing network of employee resource groups
• Employee referral program
• Employee Assistance Program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed