Senior Manager, Data Engineer
Lovelytics
- Toronto, ON
- $135,000-185,000 per year
- Permanent
- Full-time
- Gather and understand requirements from clients to develop a creative and effective technical solution, including at times leading the technical aspect of sales/presales conversations.
- Foster a collaborative work environment on your team, providing direct guidance, assignments, and overall performance and professional development for direct reports.
- Ensure accurate project allocations, forecasting, and ensuring other administrative tasks are completed across the team.
- Establish data governance frameworks, ensuring compliance across all engagements.
- Continue to expand knowledge, and stay up to date on the newest technology, trends, and best practices.
- Apply your skills with Databricks, using Python, and big data streaming to pioneer client technologies and data
- Manage projects to ensure project milestones are reached within the given timeline and budget allocated
- Support other team members on projects, which can oftentimes mean wearing many different hats
- Integrate Databricks with 3rd-party applications to support customers' architectures
- Troubleshoot complex data issues on the fly with prospects and clients
- B.S. in Computer Science or equivalent, MS preferred.
- 6+ years in data engineering working with cloud-based data analytics architectures and 3+ years of experience working in a consulting/professional services organization.
- At least 2 year directly managing a team, providing feedback and career development.
- Experience leading successful migration of complex data architecture from on-premises to cloud environments.
- Extensive knowledge of data warehousing and data lake concepts and hands-on experience deploying pipelines using Databricks
- Experience developing Machine Learning models or ML Ops processes a plus
- Excellent communication skills are a MUST, all our employees are client-facing, and this role requires both written and verbal client management skills.
- Experience designing architectures within a public cloud (AWS or Azure)
- Hands-on experience with Big Data technologies, including Spark, Hadoop, Cassandra, and others
- Ability to extract and transform data via Python, deep exposure and understanding of data warehousing, ETL pipelines, etc.
- Overall understanding of analytics from analytic engineering to visualization tools
- Databricks Data Engineer Professional and Databricks Machine Learning Professional certifications a plus
- Exciting projects with great clients in varying departments and verticals across the world
- The ability to work closely with experienced data engineers and quickly grow and expand your skillset
- The ability to work closely with all sizes of companies, ranging from Fortune 100 to small local businesses
- A workplace where you are encouraged to challenge the status quo and develop new technologies, methodologies, and processes
- A diverse team consisting of data gurus, experience seekers, and entrepreneurial minds that are always pushing to be better