Senior Data Engineer - Forward deployed
WFA Digital Insight
The demand for skilled data engineers continues to rise, with a 25% increase in remote data engineering roles in the past year. As companies like Andela scale their cloud infrastructure, they need experts who can design and implement data pipelines, ensuring seamless data flow and actionable insights. With the growth of the automotive industry's investment in data analytics, this Senior Data Engineer role is an exciting opportunity for someone who enjoys working with customers and thrives in a collaborative environment. Before applying, candidates should be aware that this role requires a strong foundation in data engineering, excellent problem-solving skills, and the ability to work independently in a remote setting.
Job Description
About the Role
As a Senior Data Engineer at Andela, you will be forward-deployed with an enterprise-scale organization in the automotive industry, playing a crucial role in their significant transformation in leveraging data and analytics to drive commercial and operational decisions. Your expertise will be key in designing and implementing modern data infrastructure, advanced analytics, and AI/ML capabilities to improve performance across key business areas.The environment emphasizes strategic thinking, cross-functional collaboration, and the ability to translate complex data into actionable insights. You will be working closely with the Data Architect to implement a unified data model, ensuring data is reliable, accessible, and structured to enable self-service analytics across the organization.
What You Will Do
- Build and maintain Snowflake data pipelines for Dealer 360 and Aftermarket workstreams
- Design and implement the dealer and aftermarket feature stores (Layer 1–2)
- Build ingestion pipelines for all external data sources
- Write and maintain dbt models for data transformation, cleaning, and normalization
- Enforce schema validation, data quality checks, and freshness SLAs across all feeds
- Collaborate with the Data Architect to implement the unified data model
- Produce documented data lineage for every pipeline before any model is trained against it
- Ensure data is structured to enable self-service analytics across the organization
- Work closely with internal stakeholders to understand data requirements and provide data-driven insights
- Stay up-to-date with industry trends and emerging technologies in data engineering
What We Are Looking For
- 8+ years of experience in data engineering on cloud platforms
- Strong expertise in Snowflake, including data modeling and query optimization
- Experience with dbt models for data transformation, cleaning, and normalization
- Excellent problem-solving skills, with the ability to break down complex problems into manageable parts
- Strong communication skills, with the ability to translate complex technical concepts into actionable insights
- Experience working with customers, understanding their data needs, and providing tailored solutions
- Ability to work independently in a remote setting, with minimal supervision
- Strong foundation in data engineering principles, including data pipelines, data warehouses, and data lakes
- Experience with cloud-based data platforms, including AWS, Azure, or Google Cloud
Nice to Have
- Experience with other cloud-based data platforms, such as AWS, Azure, or Google Cloud
- Familiarity with emerging technologies in data engineering, such as serverless computing or cloud-native data platforms
- Experience working in the automotive industry, or with similar enterprise-scale organizations
- Knowledge of AI/ML capabilities and their applications in data engineering
Benefits and Perks
- Competitive salary and benefits package
- Opportunity to work with a fast-growing company in the tech industry
- Collaborative and dynamic work environment, with a team of experienced professionals
- Flexible working hours and remote work arrangements
- Access to cutting-edge technologies and tools in data engineering
- Professional development opportunities, including training and mentorship programs
- Recognition and rewards for outstanding performance and contributions to the company
How to Stand Out
- To stand out in your application, make sure to highlight your experience with Snowflake and dbt models, and provide specific examples of how you've applied these skills in previous roles.
- Be prepared to discuss your approach to data engineering, including your experience with data pipelines, data warehouses, and data lakes.
- Show your passion for data-driven insights and your ability to communicate complex technical concepts to non-technical stakeholders.
- Familiarize yourself with the company's technology stack and be prepared to discuss how you can contribute to their data engineering efforts.
- Don't be afraid to ask questions during the interview process, and be prepared to provide examples of your problem-solving skills and experience working in a remote setting.
- Make sure to review the company's website and social media channels to get a sense of their culture and values, and be prepared to discuss how you can contribute to their mission.
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