Senior Database Engineer

Acrisure•Oklahoma City, OK

1d•Onsite

About The Position

The Lead Data Engineer is a senior individual contributor (IC) on the Auris Data Engineering team, serving as the technical anchor for the team’s database and pipeline platform. This role is responsible for designing, building, and optimizing data solutions across Oracle, Azure SQL, and Snowflake—while also providing backup Oracle DBA coverage. The ideal candidate brings hands-on expertise in SQL engineering, ELT pipeline development, and dbt, with the ability to lead through technical excellence, mentor peers, and deliver reliable, high-quality data products that power Auris’s payroll and HR platform.

Requirements

7+ years of hands-on SQL development experience in a professional data engineering or database engineering role.
5+ years of Oracle database experience including PL/SQL development and DBA-level operational tasks (backups, recovery, performance tuning).
3+ years of Snowflake experience including data modeling, performance optimization, and Snowflake-native features (Streams, Tasks, Snowpipe, Dynamic Tables).
3+ years of Azure SQL Database or SQL Server experience in cloud or on-premises environments.
3+ years of dbt (data build tool) experience—dbt Core or dbt Cloud—building and maintaining production-grade transformation models.
Experience building and operating ELT/ETL pipelines in a modern cloud data stack.
Familiarity with version control (Git / Azure DevOps) and CI/CD pipelines for database deployments.
Working knowledge of Python or shell scripting for pipeline automation and tooling.

Nice To Haves

Advanced SQL proficiency across Oracle PL/SQL, T-SQL (Azure SQL / SQL Server), and Snowflake SQL.
Strong understanding of ELT architecture patterns, data warehouse design, and dimensional modeling (star/snowflake schema).
Proficiency with dbt: model design, ref/source resolution, Jinja macros, incremental strategies, and dbt docs.
Experience with data orchestration platforms such as Azure Data Factory (ADF) or Apache Airflow.
Understanding of data governance, data quality frameworks, and observability practices (e.g., Great Expectations, Monte Carlo, dbt tests).
Oracle Certified Professional (OCP) or Snowflake SnowPro Core / Advanced: Data Engineer certification is a plus.
Microsoft Certified: Azure Data Engineer Associate or Azure Database Administrator Associate is a plus.
Experience in payroll, HR technology, financial services, or InsurTech domain preferred.
Prior experience contributing to Oracle-to-cloud migration projects is a plus.

Responsibilities

Design, develop, and optimize complex SQL queries, stored procedures, functions, triggers, and views across Oracle (PL/SQL), Azure SQL (T-SQL), and Snowflake SQL.
Conduct query performance analysis and tuning using execution plans, indexing strategies, partitioning, and statistics management.
Establish and enforce SQL coding standards, naming conventions, and code-review processes across the team.
Architect and develop ELT pipelines that ingest, transform, and serve data across Oracle, Azure SQL, and Snowflake.
Build, maintain, and govern dbt models (sources, staging, intermediate, mart layers) following modular, tested, and documented design principles.
Implement dbt schema tests and custom data quality tests to embed data quality gates into every pipeline.
Collaborate with Analytics and Data Engineering teams to translate business logic into reliable, version-controlled transformation code.
Leverage orchestration tools (Azure Data Factory or equivalent) to schedule and monitor pipeline execution.
Design and manage Snowflake objects: databases, schemas, virtual warehouses, stages, streams, tasks, and dynamic tables.
Implement Snowflake performance best practices including clustering keys, materialized views, result cache, and warehouse right-sizing.
Develop and maintain Azure SQL databases; tune workloads using Query Store and Intelligent Query Processing.
Support Snowflake and Azure SQL security configurations including RBAC, TDE, Row-Level Security, and Dynamic Data Masking.
Serve as backup Oracle DBA for production and lower environments (Oracle 19c/21c).
Perform DBA tasks: tablespace management, RMAN backup & recovery, patching coordination, and AWR/ASH performance analysis.
Diagnose Oracle performance issues using SQL Tuning Advisor, execution plans, and SQL Monitor.
Support Oracle-to-cloud migration efforts including schema conversion and data validation.
Act as technical lead and SME for SQL development and database engineering across project teams.
Mentor junior and mid-level engineers through code reviews, pairing sessions, and documentation.
Contribute to CI/CD integration of database changes using tools such as dbt Cloud, Flyway, or GitHub Actions.
Participate in sprint planning, architecture reviews, and cross-functional data initiatives.