Senior Data Engineer

About DataNimbus:
DataNimbus is a pioneering enterprise and payments modernization company, offering innovative solutions to orchestrate financial journeys for businesses worldwide. With an unwavering commitment to unlocking the value of automation and data science to increase revenue and reduce operational costs and risks, DataNimbus is at the forefront of driving innovation within the payments industry.

Why join DataNimbus:
At DataNimbus, we are committed to pushing the boundaries of what is possible in the world of payments. Our forward-thinking solutions pave the way for a smarter and more agile future. Collaborate with a dynamic team of experts and work on groundbreaking projects that shape the future of digital commerce. Embrace the future of payments modernization and become a catalyst for change with us.

Our core values of Creative Solutioning, People First, Collaboration, and Transparency form the foundation of our vibrant and inclusive work culture. We believe in providing strong learning and growth opportunities to all our team members, making it an ideal place for
anyone joining the company.

The impact you will have:

• Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to’s and productionalizing customer use cases.
• Work with engagement managers to scope variety of professional services work with input from the customer.
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications.
• Consult on architecture and design, bootstrap or implement customer projects which leads to a customers’ successful understanding, evaluation and adoption of Databricks.
• Support customer operational issues with an escalated level of support.
• Ensure that the technical components of the engagement are delivered to meet customer’s needs by working with the Project Manager, Architect, and Customer teams.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
• Mentor and provide guidance to junior data engineers and team members.

What we look for:

• 4+ years experience in data engineering, data architecture, data platforms & analytics.
• At least 3+ years experience with Databricks, PySpark, Python, and SQL.
• Consulting / customer facing experience, working with external clients across a variety of industry markets.
• Comfortable writing code in both Python and SQL.
• Proficiency in SQL and experience with data warehousing solutions.
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Strong understanding of data modeling, ETL processes, and data architecture principles.
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments – GitHub, Azure DevOps, Azure Pipelines.
• Working knowledge of MLOps methodologies.
• Design and deployment of performant end-to-end data architectures.
• Experience with technical project delivery – managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Good to have Databricks Certifications.
• Strong communication and collaboration skills.
• Excellent problem-solving skills.