- The Staff Data Engineer is responsible for Software Development Engineering and performing work in the following areas.

- Data Engineering & Data Modelling.

- Creating data architectures and logical/physical data models for databases and data warehouses.

- Forge trusted partnerships and be an integral part of Data Engineering, Data Architecture & Platforms and Data Science teams to adopt, scale and build data products.

- Data Warehouse Development & Administration.

- Designing, developing, implementing, and maintaining a data warehouse to integrate data from various sources/systems within an organization.

- Developing strategies for data acquisition, archive recovery, and database implementation.

- Managing data migrations/conversions and troubleshooting data processing issues.

- Focus on execution & delivery of highly reliable, high-quality data pipelines aimed at maximizing business value through data products.

- Lead data engineering teams, building and improving next generation data & analytics capabilities within DevSecOps framework.

Key Responsibilities :

Main accountabilities includes :

- Designing, building, and maintaining data products and pipelines.

- Developing and deploying data models.

- Monitoring and troubleshooting data systems.

- Working with product owners, data scientists and other stakeholders to understand the business needs and to build data solutions that meet those needs.

- Keeping up with the latest trends in data engineering.

- Providing training on data engineering concepts and techniques to other members of the team.

- Writing documentation for data pipelines and data models.

- Participating in data governance initiatives.

Required Qualifications :

- What We Are Looking For Typically requires a minimum of 12 years of related experiences with a Bachelor's degree in Computer or Software Engineering; or 7 years and a Master degree in Computer or Software Engineering;.

- Demonstrated strength in examining issues, driving resolution & influencing effectively across the organization.

- Ability to challenge the status quo in technology & architecture.

- Superb interpersonal & communication skills (oral and written), including the ability to explain digital concepts and technologies to business leaders, as well as business concepts to technologists.

- 3+ years leading data engineering teams in Consumer/Healthcare Goods companies and excellent understanding of business domains within the industry.

- 8-10 years of progressive experience with developing full stack Data Frameworks: ETL/ELT, data analysis, compute & storage, data pipelines, orchestration.

- Minimum of 3 years hands-on experience in Cloud Architecture (Azure, GCP, AWS) & cloud-based databases (Synapse, Databricks, Snowflake, Redshift) and various data integration techniques (API, stream, file) using DBT, SQL/PySpark, Python.

- 3+ years implementing data pipelines enabling data products through data mesh / fabric concepts.

- Minimum of 3 years leading data engineering teams with planning and execution using Agile methodology (Scrum/Kanban) within DevSecOps model.

- Ability define data pipelines to address data challenges: different granularity, data gaps, sophisticated matching logic, multi-language, structured & unstructured; harmonization & normalization of data.

- Proven track record leading multiple high-profile projects with demanding deadlines, changing requirements, and working with defined resources.

- Ability to estimate required effort and prioritize work items appropriately.

- Thrives on a diverse company culture, celebrating the uniqueness of our employees and committed to inclusion.

- Proud to be an equal opportunity employer.

- Risk Management: Identify potential risks and challenges related to data and AI products and develop mitigation plans.

Desired Qualifications :

- Conversant with Data & Analytics product management, Azure, SQL, Data Catalog.

- Experience with unstructured data processing and real-time data pipelines.

- Preferably from Retail or CPG industry.