DataNimbus

Benefits:

• Opportunity to work on cutting-edge data and AI projects

• Collaborative and innovative work environment

• Competitive salary and benefits package

• Professional growth and development opportunities

Education Requirements:

• Bachelor’s degree in Business Administration, Management, or a related field

Experience Requirements:

• 10+ years; hands-on

• 7+ years of experience managing IT or data platform projects, with at least 2 years focused on cloud-based data platforms like Databricks, AWS, Azure, or GCP

• 4+ years experience in data engineering, data architecture, data platforms & analytics

• At least 3+ years experience with Databricks, PySpark, Python, and SQL

Other Requirements:

• Building microservices using Java/Spring boot/OAuth,OIDC2/REST/SOAP

• Enterprise Integration (Apache Camel), Spring Integrator, Mule/TIBCO/IIB

• Working experience in messaging technology – Kafka/IBM MQueue

• Cloud environment (preferably Azure or AWS)

• Containerization (Docker) & deployment (Kubernetes)

• DevOps (Jenkins/Gitlabs/Azure DevOps etc.)

• Exposure to DBMS technology such as SQL. MongoDB (NoSQL) would be a plus

• Strong in Engineering practices (ex: TDD/BDD, Unit Testing, SONARQube, CI-CD etc., )

• (Nice to have) Strong Knowledge using Transformation Tools, like XSLT

• 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 timeline

• Experience working with clients and managing conflicts

• Good to have Databricks Certifications

• Strong communication and collaboration skills

• Ability to travel up to 30% when needed

• Familiarity with Databricks, Spark, or similar big data frameworks

• Understanding of data engineering, machine learning workflows, and cloud infrastructure

• Proven track record in managing multiple projects simultaneously, adhering to deadlines and budgets

• Strong understanding of Agile, Scrum, and Waterfall methodologies

• Experience working with data governance, analytics, or AI/ML projects

• Familiarity with Databricks features such as Delta Lake, MLflow, and Unity Catalog

• Understanding of data integration tools like Apache Airflow, Informatica, or Talend

Responsibilities:

• Design, develop, deliver and maintain shared engineering platforms, products and solutions

• Contribute to design and standards that will enable the development team to produce highly functional, sustainable, scalable and high performing solutions meeting or exceeding customer expectations

• Collaborate with business teams, other technical leaders, software engineers, architects in order to identify the right architecture and design while developing software platforms, products and solutions

• Communicate software architecture & design ideas effectively to other software engineering staff members through code and textual and pictorial documentation as needed

• Assume Ownership and Accountability of the work delivered by the Team

Benefits:

• Opportunity to work on cutting-edge data and AI projects

• Collaborative and innovative work environment

• Competitive salary and benefits package

• Professional growth and development opportunities

Experience Requirements:

• 7+ years of experience managing IT or data platform projects, with at least 2 years focused on cloud-based data platforms like Databricks, AWS, Azure, or GCP

Other Requirements:

• Familiarity with Databricks, Spark, or similar big data frameworks

• Understanding of data engineering, machine learning workflows, and cloud infrastructure

• Proven track record in managing multiple projects simultaneously, adhering to deadlines and budgets

• Strong understanding of Agile, Scrum, and Waterfall methodologies

• Experience working with data governance, analytics, or AI/ML projects

• Familiarity with Databricks features such as Delta Lake, MLflow, and Unity Catalog

• Understanding of data integration tools like Apache Airflow, Informatica, or Talend

Responsibilities:

• Develop detailed project plans, including timelines, milestones, and resource allocation

• Define project scope and objectives, involving all relevant stakeholders and ensuring technical feasibility

• Act as the primary point of contact for clients, providing updates and addressing concerns promptly

• Collaborate with Databricks consultants, data engineers, data scientists, and client teams to ensure alignment with project goals

• Identify potential risks and issues early, developing mitigation and contingency plans

Benefits:

• Opportunity to work on cutting-edge data and AI projects

• Collaborative and innovative work environment

• Competitive salary and benefits package

• Professional growth and development opportunities

Experience Requirements:

• 4+ years experience in data engineering, data architecture, data platforms & analytics

• At least 3+ years experience with Databricks, PySpark, Python, and SQL

Other Requirements:

• 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 timeline

• Experience working with clients and managing conflicts

• Good to have Databricks Certifications

• Strong communication and collaboration skills

• Ability to travel up to 30% when needed

Responsibilities:

• 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