Senior Manager of Data Engineering
Edmonton, AB, United States
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Blend360
Blend360 co-creates value with leading companies through the integration of data, advanced analytics, technology & people. Get in touch with us today.Company Description
Company Description
BLEND360 is an award-winning, new breed Data Science Consultancy focused on powering exceptional results for our Fortune 500/1000 clients and other major organizations. We are a growing company—born at the intersection of advanced analytics, data, and technology.
Blend360’s rapidly expanding Data Engineering practice is seeking Data Engineering Managers who love building teams and pioneering technical solutions to solve our client’s most complex business problems. Our environment is fun, fast-paced, and collaborative.
Working at the forefront of our business, our technologists drive major projects within BLEND360 using the latest programming languages and technologies to develop innovative data driven solutions. We are looking for self-starters, who enjoy motivating and teaching others best practices within data engineering.
Job Description
Our new Senior Data Engineering Manager will be in the forefront of driving major projects within BLEND360 and working with our data engineering team to develop innovative data driven solutions that integrate distributed sources of data, perform large scale learning and reasoning, and integrate results.
Job Description
As a Senior Data Engineering Manager, your role is to spearhead the data engineering teams and elevate the team to the next level! You will be responsible for laying out the architecture of new project as well as selecting the tech stack associated with it. You will plan out the develop cycles deploying AGILE if possible as well as creating the foundations for good data stewardship with our new data products!
You will also set up a solid code framework that needs to be built to purpose, yet have enough flexibility to adapt to new business use cases—a tough but rewarding challenge!
Responsibilities:
- Collaborate with several stakeholders to deeply understand the needs of data practitioners to deliver at scale
- Lead Data Engineers to define, build and maintain Data Platform
- Work on emerging technologies, building distributed applications
- Drive development effort End-to-End for on-time delivery of high quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards.
- Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner.
- Further develop critical initiatives, such as Data Discovery, Data Lineage and Data Quality
- Lead and Mentor junior resources
- Help your team members grow in their role and achieve their career aspirations
- Build data systems, pipelines, analytical tools and programs
- Conduct complex data analysis and report on results
Qualifications
- 8+ Years of Experience
- Degree in Computer Science, Data Science, Mathematics, IT, or similar field
- 3 - 5 Years of Experience as a data engineer or similar role
- Must have experience executing projects end to end.
- Technical expertise with data models, data mining, and segmentation techniques
- Deep understanding, both conceptually and in practice of at least one object orientated library (Python, Scala)
- Strong SQL skills and a good understanding of existing SQL warehouses and relational databases.
- Strong Spark, PySpark, Spark SQL skills and good understanding of distributed processing frameworks.
- Build large-scale batch and real-time data pipelines.
- Ability to work independently and mentor junior resources.
- Desire to lead and develop a team of Data Engineers across multiple levels
- Nice to have: Cloud experience (AWS, Azure, GCP), Snowflake, Databricks, Hadoop, DBT, Elastic Search, Data modeling, Airflow, CI\CD, Agile Methodologies, Docker\Kubernetes.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow Architecture AWS Azure Computer Science Data analysis Databricks Data Mining Data pipelines Data quality Docker Engineering GCP Hadoop Kubernetes Mathematics Pipelines PySpark Python RDBMS Scala Snowflake Spark SQL Teaching
Perks/benefits: Career development
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