Lead Data Engineer

This is a fully remote position, open to applicants in Arizona, +3 more states.

📋 Description

• Oversee the design, development, and implementation of enterprise data solutions utilizing AWS Services, Snowflake, dbt, Python, SQL, and other relevant cloud technologies.

• Create and maintain data warehouses, Operational Data Stores, and ETL/ELT pipelines to support analytics, reporting, and operational data functionalities.

• Design and execute batch and real-time data processing solutions through streaming and event-driven architectures.

• Collaborate with business stakeholders, analysts, and technology teams to convert requirements into scalable data solutions.

• Establish and advocate for data quality strategies, testing standards, governance practices, and compliance controls.

• Develop testing practices that include data validation frameworks, dbt testing standards, and quality controls.

• Define standards for monitoring, observability, and operational reliability, which encompass dashboards, alerts, SLOs, and SLAs.

• Create deployment strategies, environment promotion standards, and release governance practices.

• Participate in technical discussions, peer reviews, and initiatives for knowledge sharing.

• Use AI-powered development and productivity tools to expedite delivery, enhance code quality, and boost productivity.

• Mentor engineering talent and work alongside engineers, product partners, and business stakeholders to produce enterprise data products and cloud-based data solutions.

⛳️ Requirements

• Bachelor's Degree with 6 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related fields; OR High School Diploma or GED with 10 years of experience in the same areas.

• Extensive experience with cloud platforms such as AWS, Azure, or GCP.

• Advanced knowledge of modern data warehousing and large-scale data processing technologies like Snowflake, Spark, or similar platforms.

• High proficiency in Python and SQL.

• Significant experience in designing, developing, orchestrating, and maintaining ETL/ELT pipelines and data integration solutions using dbt, Apache Airflow, Astronomer, or similar technologies.

• In-depth experience with data modeling, data warehousing, and best practices in data engineering.

• Proven track record in designing, developing, and supporting scalable, reliable, and high-performance data engineering solutions in enterprise settings.

• Experience working with business and technology stakeholders to deliver data-driven solutions.

• Familiarity with enterprise ETL/ELT tools such as DataStage, SAP BODS, SSIS, Informatica, or similar technologies is beneficial.

• Experience in developing and supporting Operational Data Stores, analytics platforms, and data products is advantageous.

• Knowledge of Snowflake Cortex, CDC, streaming, and real-time data ingestion technologies like Kafka, Amazon Kinesis, Qlik Replicate, Snowpipe Streaming, or equivalent platforms is a plus.

• Experience integrating data across AWS, on-premises, and Snowflake environments, with insight into enterprise security, governance, and compliance frameworks is a plus.

• Familiarity with Data Vault modeling and modern data warehousing methodologies is a plus.

• Experience leading technical initiatives, mentoring team members, and advocating for engineering best practices is a plus.

• Experience in Financial Services, Banking, or other highly regulated industries is a plus.

• Knowledge of Tableau, Power BI, or other analytics and visualization platforms is a plus.

• Experience utilizing AI-powered development and productivity tools is a plus.

• Relevant certifications such as AWS Certified Data Engineer, AWS Certified Solutions Architect, SnowPro Core, SnowPro Advanced Data Engineer, or equivalent are a plus.

🏝️ Benefits

• A competitive, thoughtfully crafted benefits program of high quality.

• Variable incentives, bonuses, benefits, and/or other awards may be included in the overall compensation package.