857 Azure Databricks Jobs

Responsibilities
As a member of the Platform engineering team, you will be the key techno functional expert leading and overseeing PepsiCo's Platforms & operations and drive a strong vision for how Platforms engineering can proactively create a positive impact on the business.

You'll be an empowered Leader of a team of Platform engineers who build Platform products for platform optimization and cost optimization and build tools for Platform ops and Data Ops on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company.

As Leader of the Platform engineering team, you will help in managing platform Governance team that builds frameworks to guardrail the platforms of very large and complex data applications in public cloud environments and directly impact the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics.You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems.

Accountabilities -

Active contributor to cost optimization of platforms and services.
Manage and scale Azure Data Platforms to support new product launches and drive Platform Stability and Observability across data products.
Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for Data Platforms for cost and performance.
Responsible for implementing best practices around systems integration, security, performance and Platform management.
Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.
Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.
Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners.
Develop and optimize procedures to production Alize data science models.
Define and manage SLAs for Platforms and processes running in production.
Support large-scale experimentation done by data scientists.
Prototype new approaches and build solutions at scale.
Research in state-of-the-art methodologies.
Create documentation for learnings and knowledge transfer.
Create and audit reusable packages or libraries.

11+ years of overall technology experience in Program management, and data engineering
4+ years of experience with Data Lake Infrastructure, Data Warehousing, and Data Analytics tools.
4+ years of experience in Databricks optimization and performance tuning
Experience in managing multiple teams and coordinating with different stakeholders to implement the vision of the team.
Fluent with Azure cloud services. Azure Certification is a plus.
Experience with integration of multi cloud services with on-premises technologies.
Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
Experience with at least one MPP database technology such as Redshift, Synapse or SnowFlake.
Experience with version control systems like Github and deployment & CI tools.
Experience with Azure Data Factory, Azure Databricks.
Experience with Statistical/ML techniques is a plus.
Experience with building solutions in the retail or in the supply chain space is a plus
Understanding of metadata management, data lineage, and data glossaries is a plus.
Working knowledge of agile development, including DevOps and DataOps concepts.
Familiarity with business intelligence tools (such as PowerBI).

Education

BE/B tech in Computer Science, Math, Physics, or other technical fields.
Skills, Abilities, Knowledge
Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate
confidence in communications with senior level management.
Proven track record of leading, mentoring data teams.
Strong change manager. Comfortable with change, especially that which arises through company growth.
Ability to understand and translate business requirements into data and technical requirements.
High degree of organization and ability to manage multiple, competing projects and priorities simultaneously.
Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment.
Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs.
Foster a team culture of accountability, communication, and self-management.
Proactively drives impact and engagement while bringing others along.
Consistently attain/exceed individual and team goals
Ability to lead others without direct authority in a matrixed environment.
Competencies
Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in
the business.

Understands both the engineering and business side of the Data Products released.
Places the user in the center of decision making.
Teams up and collaborates for speed, agility, and innovation.
Experience with and embraces agile methodologies.
Strong negotiation and decision-making skill.
Experience managing and working with globally distributed teams.