Our team works in a fun, innovative, and challenging environment that directly influences the strategic direction and performance of the Marketing, Strategy & Data Insights team in our Home Solutions and Mobility business.
We provide opportunities for you to excel and show your stuff: work on high-value and high-visibility projects. We have flexible work styles with the ability to work in and out of the office. You will work in a team that actively supports your personal development with progressive training and development tools.
This is a remote role with occasional visits to the office.

QUALIFICATIONS

• 6+ years Data Engineering experience.
• 4 years data platform solution architecture and design.
• You are a collaborative, creative, open-minded individual who possesses a natural curiosity and desire to experiment.
• Proficiency in:
• Programming language experience (java/python - including low code tools such as Informatica, Datastage or equivalent).
• SQL and database proficiency (min 3 years).
• Task automation - setting up DAGS in Control-M, Apache Airflow, Prefect, etc.
• Unix scripting.
• Quality Assurance & Site Reliability Engineering.
• Infrastructure as code (e.g. Terraform, Pulumi, Puppet, Ansible).
• Data Modeling.
• Working Knowledge of ML Ops.

EDUCATION AND PROFESSIONAL DESIGNATION / CERTIFICATION

• Bachelor’s Degree in Software Engineering, Computer Science or related field.
• Data engineering certification.
• GCP certification.
• Analytics - BI or AI/ML.

• You will demonstrate sound engineering principles and a good understanding of modern CI/CD toolsets.
• Design and build data extraction, loading and transformation pipelines and data products across on-prem and cloud platforms.
• Perform application impact assessments, requirements reviews and develop work estimates.
• Develop test strategies and site reliability engineering measures for data products & solutions.
• Lead resolution of critical operations issues including post-implementation reviews.
• Perform technical data stewardship tasks including metadata management, security and privacy by design.
• Being action-oriented, ensuring accountability, driving results, being collaborative and communicating.
• effectively, will be essential Research, construct, develop, and test complex ETL pipeline.
• Apply automation and monitoring tools using a test-driven approach and mindset.
• Develop and maintain scalable data infrastructure that provides an outstanding experience for internal stakeholders and enables consistent value extraction from data Innovate data ingestion and processing methods to support strategic priorities and facilitate decision-making throughout the organization.
• Build and scale data infrastructure that powers batch and real-time data processing of thousands of records daily.
• Interface with data scientists, analysts, product managers and all data stakeholders to understand their needs and promote best practices.
• Architect data pipelines that provide fast, optimized, and robust end-to-end solutions.
• Drive and maintain a culture of quality, innovation and experimentation.