Enterprise data engineering manager

job summary:
This is an onsite position in San Diego, CA.

The Data Engineering Manager will be responsible for managing various key data implementations across the organization and providing people and technology leadership. They will perform data architecture analysis, design, development, and testing to deliver data applications, services, interfaces, ETL processes, reporting, and other workflow and management initiatives.

This role requires a highly motivated individual with strong leadership capability, technical ability, data capability, excellent communication, and collaboration skills, including the ability to develop solutions for and troubleshoot a diverse range of problems.

location: San Diego, California
job type: Permanent
salary: $165,000 - 180,000 per year
work hours: 8am to 5pm
education: Bachelors


responsibilities:

• Head the development and delivery of enterprise-scale, mission-critical data platforms (e.g., Databricks Lakehouse, GCP services) to meet critical business priorities.
• Establish the roadmap and vision for enterprise-scale data engineering; execute on this roadmap to deliver shared frameworks for the broader enterprise application development teams.
• Build technical excellence by defining and implementing robust data engineering standards and quality frameworks that govern data pipeline development, testing, and deployment across the data platform.
• Establish, enforce, and champion modern DataOps and CI/CD practices within the team. Lead the automation of deployment, testing, and monitoring to accelerate delivery speed and ensure data quality.
• Provide technical leadership and hands-on guidance to the Data Engineering team to ensure timely and high-quality project delivery and enhancements. Mentor engineers in advanced PySpark, SQL, dbt, Fivetran, and cloud-native development to maximize team output.
• Collaborate with multiple teams, understand the overall enterprise Data Architecture, and develop end-to-end solutions for data sourcing, data processing/integration, data provisioning, and delivery.
• Deliver projects to successful completion as defined by predetermined project success criteria, including those established by the business, ensuring that projects are delivered on time and within budget.
• Focus on designing and developing highly scalable, efficient, and reliable data infrastructure to scale and compute to meet business objectives.
• Lead, coach, and develop the team while creating a clear vision. Educate cross-functional teams on how to leverage data to identify opportunities to increase revenue and performance.
• Drive IT solutions to ensure they meet business needs balanced with a pragmatic and integrated approach to the design of technical solutions.
• Remain up-to-date on key technology, business, and industry trends.
• Perform other duties and responsibilities as assigned.

qualifications:
- Bachelor's degree in Computer Science, MIS, or a related field.

- 10+ years of experience managing Data Engineering and leading Technology Teams.

- 7+ years working with SQL Server and other DB management systems within Cloud and on-prem data ecosystems.

o 7+ years working with cloud-native data ecosystems (GCP, Azure, AWS) with deep experience in Cloud Data Warehouses (e.g., BigQuery, Snowflake, Databricks), exposure to various database types (SQL and NoSQL), and on-prem databases including SQL Server.

- Expertise in Databricks and the Spark ecosystem, including designing and optimizing pipelines using PySpark, implementing modern data architecture, and strong hands-on experience.

o Advanced-level experience with Python and PySpark (for data processing), advanced SQL, and modern ELT/ETL tools (e.g., Fivetran and dbt).

o Strong experience with a breadth of Data Integration tools, Databases, Big Data Platforms, Cloud-based data platforms, and Data Streaming technologies.

- Experience leading technical teams (e.g., Data Engineers, Tech Leads), including mentoring, project oversight, and setting technical direction.

- Expertise within Data Architecture and, most importantly, a deep understanding of overall enterprise data and the ability to understand data in the context of business goals.

- Proficient in building a modern, next-generation Lakehouse platform from the ground up.

- Experience in enterprise implementation, leadership, strategic planning, and strong business acumen.

- Experience within the Financial Services industry.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact View email address on click.appcast.io.


Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).


This posting is open for thirty (30) days.

Qualified applicants in San Francisco with criminal histories will be considered for employment in accordance with the San Francisco Fair Chance Ordinance.


Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.


We will consider for employment all qualified Applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.