Data Engineer at Equinix implementing data architecture solutions for scalability and analytics. Collaborating with teams to design data pipelines and maintain data models for business objectives.
About the role
- Senior Manager overseeing AI/ML solutions and technical leadership in a tax services firm. Responsible for data implementation, team management, and high-performance technology solutions.
Responsibilities
- Overseeing the implementation of technical solutions for the identification of complex patterns in large, high-dimensional/high-frequency data sets.
- Executing and participating in the data vision.
- Building out robust, high-performance technology solutions.
- Mixing strong hands-on technical leadership with the management of matrixed resources and multiple teams.
- Developing code and the skills of the team at large.
- Leading an agile team to design, develop, test, implement, and support highly scalable AI/ML solutions.
Requirements
- 7+ years of professional experience in data science, machine learning, or applied analytics.
- Proven experience leading high-performing teams of data scientists, ML engineers, data engineers, or other data and analytics professionals.
- Hands-on experience designing, building, and deploying enterprise ML solutions to production, including end-to-end model lifecycle ownership (not prototypes only).
- Strong coding experience in Python (required) with experience overseeing or contributing to solutions written in Java, Scala, or C.
- Direct experience building cloud-based data and ML solutions using AWS or Azure.
- Experience designing, deploying, and maintaining production data pipelines.
- Hands-on experience with at least one ML framework, such as TensorFlow, PyTorch, or Scikit-learn.
- Strong system and data architecture skills, including the ability to design ML systems, create data models, develop architecture diagrams, and define system components.
- Experience working in mixed Windows and Linux environments.
Benefits
- 14-Weeks of 100% Paid Leave for New Parents (Adoption Included)
- Monthly Gym Membership Reimbursement OR Gym Equipment Reimbursement
- 401K with Employer Match
- Tuition Reimbursement After One Year of Service
- Fertility Assistance Program
- Four-Week Company-Paid Sabbatical Eligibility After Five Years of Service
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Warehouse Architect developing and optimizing robust data warehouse environments on SAP BW/4HANA. Critical for enabling advanced analytics and reporting across the organization.
Data Engineering Manager leading a new Data Engineering team in Bengaluru. Shaping the design and scaling of core data engineering practices across the organization.
Sr. ETL/Data Warehouse Lead at Huntington designing, developing, and supporting ETL and Data Warehousing framework. Analyzing systems based on specifications and providing technical assistance.
Senior Google Data Architect designing and delivering scalable data solutions on Google Cloud Platform. Collaborating across teams to shape target - state data architectures and influence enterprise data strategy.
Data Engineer developing scalable data lake solutions and optimizing data pipelines at U.S. Bank. Collaborating with teams to manage data governance and cloud migration activities.
Lead AI, MLOps & Data Engineer at WedR, guiding complex data projects and AI innovation. Collaborate with diverse experts in a Product Studio for digital transformations.
Lead Azure Databricks Data Engineer implementing data solutions for data engineering projects at Ryan Specialty. Collaborating with stakeholders and mentoring junior staff on data pipelines and ETL processes.
Lead Azure Databricks Data Engineer at Ryan Specialty focused on implementing data solutions and collaborating with cross - functional teams to enhance data architecture.
Senior Data Engineer designing and implementing sustainable data solutions for diverse clients. Collaborating closely with stakeholders to enhance data services and platforms in a hybrid environment.