Senior Data Engineer

About DataNimbus

Data and AI

responsible innovation, adaptability, and customer-centricity

Why Join DataNimbus

sustainable, AI-driven future

• Work with cutting-edge technologies and

  revolutionize workflows in Data+AI solutions.

• Contribute to solutions that are

  trusted by global businesses

  for their scalability, security, and efficiency.

• Grow personally and professionally

  in a culture that values curiosity and continuous learning.

DataNimbus is the place for you.

Key Responsibilities:

• Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-tos 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 customers 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.

Required Qualifications:

• 5+ years experience in data engineering, data architecture, data platforms & analytics.
• At least 4+ 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.

Interested

Send in your CV to [HIDDEN TEXT] ASAP!