SunnyData

Data Engineer

• You will be part of a team responsible for supporting new and existing customers in their data engineering needs.
• You will guide customers to make the best technical decisions to achieve their goals
• You will actively work across multiple customer accounts which you would need to track and report on their progress.
• You will design, build, and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing /quality solutions.
• You will analyze sources to determine value and recommend data to include in analytical processes.
• You will incorporate core data management competencies including data governance, data security and data quality.
• You will collaborate within and across teams to support delivery and educate end users on data products / analytic environments.
• You will perform data and system analysis, assessment and resolution for defects and incidents of moderate complexity and correct as appropriate.
• You will test data movement, transformation code, and data components.

Senior Data Engineer

Solutions Engineer

• Customer Engagement: Serve as a trusted advisor to customers, guiding them through their data engineering and data architecture needs with a focus on Databricks solutions. In this role you will split your time evenly between billable and pre-sales activity.
• Technical Leadership: Design, build, and deploy comprehensive data solutions that capture, transform, and leverage data to support AI, ML, and business intelligence initiatives.
• Pre-Sales Support: Collaborate with sales teams to present technical solutions to prospective clients, demonstrating the value of SunnyData's offerings.
• Project Oversight: Manage multiple customer accounts, ensuring timely delivery of solutions and tracking progress to report outcomes.
• Solution Design: Architect data solutions, incorporating best practices in data governance, security, and quality.
• Data Analysis: Evaluate data sources for their value, recommending data inclusion strategies to enhance analytical processes.
• Cross-Functional Collaboration and Leadership: Lead internal teams, provide direction and mentorship to project teams to deliver solutions and educate end users on data products and analytic environments.
• Problem Resolution: Perform system analysis, assess and resolve data and system defects, and apply appropriate corrections.
• Quality Assurance: Test data movement, transformation code, and data components to ensure accuracy and reliability.

Solutions Architect – Platform, Cloud Infrastructure, Security

Senior Data Engineer, Contractor – Financial Services

Data Analyst

• Improved decision-making: Translate complex data into clear, reliable, and actionable dashboards that support faster, data-driven business decisions.
• Performance optimization: Advanced knowledge of DAX, Dataflows, partitioning, and large-scale data modeling ensures high-performance reporting and reduced load times.
• Standardization and scalability: Bring structure to BI practices by implementing version control, modeling standards, and scalable design using tools like Tabular Editor and Git.
• Stronger business collaboration: Act as a bridge between technical teams and business stakeholders, aligning data solutions with business needs more effectively.
• Team development: Support and mentor junior analysts, contributing to team growth and raising the overall technical bar.

Power BI Data Analyst, Contractor

• Be part of a team responsible for supporting new and existing customers in their data engineering needs.
• Guide customers to make the best technical decisions to achieve their goals.
• Actively work across multiple customer accounts which you would need to track and report on their progress.
• Design, build and operationalize complex data solutions, fix issues, apply transformations, and recommend data cleansing / quality solutions.
• Analyze data sources to determine their value and recommend them to include in analytical processes.
• Incorporate core data management competencies including data governance, data security and data quality.
• Collaborate within and across teams to support delivery and educate end users on data products / analytic environments.
• Perform data and system analysis, assessment and resolution for defects and incidents of moderate complexity and correct as appropriate.
• Test data movement, transformation code, and data components.

Administration

• Own, optimize, and secure the Databricks environment, ensuring scalable, reliable, and well-monitored performance for data and ML workloads.
• Enable and optimize data and ML workflows in Databricks, enhancing self-service capabilities and supporting Unity Catalog for governance and discovery.
• Implement and maintain Databricks security, access controls, and compliance practices, ensuring least-privilege governance and alignment with enterprise standards.
• Partner with data and ML teams to improve the Databricks platform, drive best practices and automation, and coordinate with DevOps on cloud infrastructure and integrations.

Databricks Platform Administrator

Technical Project Manager

• Keep the team organized and moving: Coordinate meetings, ceremonies, and project logistics to ensure teams remain aligned and productive.
• Maintain communication clarity: Capture notes, decisions, and action items during client and internal meetings, and share updates promptly with stakeholders.
• Support tracking and follow-up: Monitor action items, dependencies, and deadlines, following up with the appropriate owners to maintain delivery momentum.
• Enable effective collaboration: Facilitate smooth communication between cross-functional teams (technical leads, engineers, client stakeholders), helping reduce friction and misunderstandings.
• Identify project risks and roadblocks: Proactively monitor and work with the technical team to provide solutions to keep the engagement on track.
• Promote lightweight agile practices: Support the team in using simple, effective agile habits such as ceremonies, visual boards, and feedback loops, to improve predictability and transparency.