Data Engineering Team Manager - American Honda Motor Co Inc

At Honda, The Power of Dreams drives us to create intelligent products that enhance mobility and increase the joy in people’s lives.

We continue to draw inspiration from the visionary ideas of our namesake, Soichiro Honda. He saw incredible power in the freedom of mobility and used his imagination to change the world. It is this mindset that guides us to help move people forward and protect the future we all share.

We strive to earn the trust and support of the many diverse communities we happily serve, and we’ll always remember who’s in the driver’s seat on the way to a better world for all.

What Makes a Honda, is Who makes a Honda
Honda has a clear vision for the future, and it’s a joyful one.  We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success.  We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”

We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.

If your goals and values align with Honda’s, we want you to join our team to Bring the Future!

Job Purpose

• The role of a Data Engineering Team Manager is to lead and manage a team of data engineers in designing, developing, maintaining, and supporting the organization's data pipelines. Here are some key responsibilities for the Data Engineering Team Manager:
• Team Leadership: Manage and provide leadership to a team of data Engineers, ensuring effective collaboration and coordination among team members. Set clear goals, provide guidance and mentorship, and evaluate individual and team performance.
• Data Engineering roadmap: Develop and maintain a robust data engineering strategy and roadmap that aligns with the organization's overall business objectives. This includes selecting and operationalizing data engineering tools, defining data engineering standards, and ensuring data integrity, security, and quality is maintained.
• Data Governance and Data Catalog: Adhere to data governance and data Catalog policies, procedures, and best practices on the data pipelines. Collaborate with governance and Catalog teams to define data standards, data classification, data retention, and data lifecycle management.
• Data Integration Pipeline: Design and implementation of data integration processes, ensuring seamless data flow and interoperability between systems. Work closely with application developers and infrastructure teams to ensure effective data integration and transformation.
• Data Security and Privacy: Ensure the implementation of data security and privacy measures, in compliance with relevant regulations (such as GDPR, HIPAA, etc.), to protect sensitive data from unauthorized access or breaches.
• Data Analytics and Reporting: Collaborate with business analysts and data scientists to define data requirements for analytics and reporting purposes. Support the development and maintenance of data analytics platforms, data warehouses, and reporting solutions.
• Stakeholder Engagement: Engage with business stakeholders, including executives, managers, and end-users, to understand their data needs and provide strategic recommendations. Collaborate with cross-functional teams to define and execute data-driven initiatives.
• Vendor Management: Evaluate and select third-party vendors or solutions for data-related products or services. Manage vendor relationships, contracts, and service level agreements (SLAs) to ensure successful delivery.
• Continuous Improvement: Stay updated with emerging data management trends, technologies, and best practices. Identify opportunities for process improvement, automation, and optimization within the data engineering team.
• Collaboration and Communication: Foster a culture of collaboration, knowledge sharing, and effective communication within the team and across departments. Facilitate regular team meetings, workshops, and training sessions to enhance technical skills and foster innovation.

• Build, lead and manage high performance team of data engineers to meet organization data needs and deliver and support project and operations with quality and customer service focus. Foster associate development by coaching, training, and mentoring.
• Work together with Unit and Dept leadership to develop and deliver long-term strategic goals for data engineering roadmaps; sense, study, test and implement new technologies and manage overall data knowledge.
• Build NA & global relationships and network to achieve trust and credibility, by discovering and meeting the needs of internal and external customers and vendors. Use persuasion and influence to achieve maximum results with Enterprise IT goals.
• Support enterprise information governance methods, stewardship and procedures for tracking data quality, completeness, redundancy, and improvement

• Hybrid: ~  3 days per workweek at the local office

#LI-Hybrid

Education: An undergraduate or graduate level degree in computer science, data sciences, information systems, computer engineering, electronics / electrical engineering or similar field of study. Certifications in Data engineering, analytics, data Science and Business Intelligence tools and technologies will be a plus.

• 8 or more years hands-on experience with data engineering, data architecture, large-scale data modeling, and business requirements gathering/analysis.
• At least 3 or more years of experience leading teams in Data engineers, Data scientists, Data Analysis, Information Management and Business Intelligence
• Experience is strategy, project, financial, performance and operations management.
• Knowledgeable, go-getter, self-driven individual with strong sense of ownership.
• Team player/collaborator who builds relation with customers and team members, earns their trust, and creates influence to meet tactical or strategic objectives.
• Servant leader who clears roadblocks for the team members to meet their deliveries and help them grow individually.
• Knowledge of project management, budgeting, financial management, vendor management, service management and operational efficiency will be a huge plus.
• Strong oral, verbal communication/presentation skills.
• Strong understanding of relational data structures, theories, and principles. Experience with database platforms, including DB2, MS SQL Server, PostgreSQL, Couchbase, MongoDB, etc.
• Knowledge in enterprise information life cycle management including enterprise repository tools, data modeling, mapping, profiling, quality and master data management practices.
• Experience in programming languages like Python, Java, Scala or others.
• Knowledge of cloud-based technology including cloud connectivity options, data storage options (S3, Glarcier), data lakes (S3 etc.), master data management, data cataloging, cloud warehouses (Redshift, etc.), cloud ETL/ELT tools (Glue, EMR etc.), cloud streaming options (Kinesis, Kafka etc.), cloud databases (RDS, DynamoDB, Redshift etc.), data search options (Athena) and cloud/on-prem BI products(Power BI, Tableau, etc.)
• Working knowledge of informatica products like PowerCenter, IICS, IDMC or BDM/DEI.
• Working knowledge of Big Data platforms technologies and processes including cloud big data products like Hives, Spark, EMR etc.

#LI-BEV

Visa sponsorship

• This position is not eligible for work visa sponsorship.

What differentiates Honda and make us an employer of choice?

 Total Rewards: 
•    Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
•    Regional Bonus (when applicable)
•    Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included)
•    Industry-leading Benefit Plans (Medical, Dental, Vision, Rx)
•    Paid time off, including vacation, holidays, shutdown
•    Company Paid Short-Term and Long-Term Disability 
•    401K Plan with company match + additional contribution
•    Relocation assistance (if eligible)

Career Growth:
•    Advancement Opportunities
•    Career Mobility  
•    Education Reimbursement for Continued Learning
•    Training and Development Programs 

Additional Offerings:
•    Lifestyle Account
•    Childcare Reimbursement Account
•    Elder Care Support
•    Tuition Assistance & Student Loan Repayment
•    Wellbeing Program
•    Community Service and Engagement Programs
•    Product Programs
•    Free Drinks Onsite

Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

Job Purpose

• The role of a Data Engineering Team Manager is to lead and manage a team of data engineers in designing, developing, maintaining, and supporting the organization's data pipelines. Here are some key responsibilities for the Data Engineering Team Manager:
• Team Leadership: Manage and provide leadership to a team of data Engineers, ensuring effective collaboration and coordination among team members. Set clear goals, provide guidance and mentorship, and evaluate individual and team performance.
• Data Engineering roadmap: Develop and maintain a robust data engineering strategy and roadmap that aligns with the organization's overall business objectives. This includes selecting and operationalizing data engineering tools, defining data engineering standards, and ensuring data integrity, security, and quality is maintained.
• Data Governance and Data Catalog: Adhere to data governance and data Catalog policies, procedures, and best practices on the data pipelines. Collaborate with governance and Catalog teams to define data standards, data classification, data retention, and data lifecycle management.
• Data Integration Pipeline: Design and implementation of data integration processes, ensuring seamless data flow and interoperability between systems. Work closely with application developers and infrastructure teams to ensure effective data integration and transformation.
• Data Security and Privacy: Ensure the implementation of data security and privacy measures, in compliance with relevant regulations (such as GDPR, HIPAA, etc.), to protect sensitive data from unauthorized access or breaches.
• Data Analytics and Reporting: Collaborate with business analysts and data scientists to define data requirements for analytics and reporting purposes. Support the development and maintenance of data analytics platforms, data warehouses, and reporting solutions.
• Stakeholder Engagement: Engage with business stakeholders, including executives, managers, and end-users, to understand their data needs and provide strategic recommendations. Collaborate with cross-functional teams to define and execute data-driven initiatives.
• Vendor Management: Evaluate and select third-party vendors or solutions for data-related products or services. Manage vendor relationships, contracts, and service level agreements (SLAs) to ensure successful delivery.
• Continuous Improvement: Stay updated with emerging data management trends, technologies, and best practices. Identify opportunities for process improvement, automation, and optimization within the data engineering team.
• Collaboration and Communication: Foster a culture of collaboration, knowledge sharing, and effective communication within the team and across departments. Facilitate regular team meetings, workshops, and training sessions to enhance technical skills and foster innovation.