Experienced Full Stack Data Engineer – Cloud Data Analytics & Science

Join arenaflex, a leading innovator in the industry, as we seek a highly skilled and experienced Full Stack Data Engineer to lead our cloud data analytics and science initiatives.

About arenaflex

arenaflex is a pioneering company that has been at the forefront of innovation, driving technological advancements and pushing the boundaries of what is possible. With a strong commitment to excellence and a passion for delivering exceptional results, we have established ourselves as a leader in our industry. Our team of talented professionals is dedicated to creating cutting-edge solutions that transform the way businesses operate and interact with their customers.

Role Snapshot

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Location:

Remote

Position:

Experienced Full Stack Data Engineer – Cloud Data Analytics & Science

Compensation:

A highly competitive salary, with a range of $160,000 to $230,000, plus a comprehensive benefits package, including stock options and restricted stock units.

Company:

arenaflex

Start Date:

Immediate openings available

Job Description

As a Full Stack Data Engineer at arenaflex, you will play a critical role in shaping the future of our cloud data analytics and science initiatives. You will be responsible for designing, developing, and deploying scalable and secure data pipelines, as well as leading a team of data engineers to achieve our business objectives.

Key Responsibilities:

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Lead and Coach a Team of Data Engineers:

Provide technical guidance, mentorship, and support to a team of data engineers, fostering a culture of continuous learning and development.

Drive Modern Software Practices:

Ensure adherence to and promote modern software practices through code reviews, design sessions, and technical workshops.

Design and Develop Data Pipelines:

Collaborate with cross-functional teams to design and develop scalable and secure data pipelines, leveraging cloud-based technologies such as ADLS, Databricks, and Delta-Lake.

Grow Top-Tier Design for Services:

Ensure that services and components are modularized, secure, reliable, diagnosable, observable, and reusable.

Develop Test Inclusion for Services:

Plan and execute integration tests, and resolve issues to ensure high-quality services.

Focus on Business Needs:

Drive business outcomes through a data-driven approach, leveraging data analytics and science to inform decision-making.

Investigate and Improve Automation, Reliability, and Monitoring:

Identify opportunities to automate, improve reliability, and enhance monitoring for deployed items.

Set the Vision for Data Analysis and Reporting:

Establish the strategic direction for data analysis and reporting, aligning with business objectives and driving business outcomes.

Plan, Develop, and Refine Complex Data Models and Reporting Structures:

Collaborate with stakeholders to design and develop complex data models and reporting structures, leveraging data analytics and science to drive business insights.

• Drive the Design and Execution of Adaptable and Effective Data Analysis and Reporting Structures: Ensure that data analysis and reporting structures are adaptable, effective, and aligned with business objectives.

Guarantee the Integrity, Security, and Performance of Data Items and Reporting Solutions:

Collaborate with data engineers, data scientists, and IT experts to ensure the integrity, security, and performance of data items and reporting solutions.

Define and Implement the Long-Term Technical Strategy for Data Analysis:

Develop and implement a long-term technical strategy for data analysis, incorporating emerging technologies and industry trends.

Stay Up-to-Date with Emerging Technologies:

Evaluate the relevance of emerging technologies to arenaflex and identify opportunities to leverage them to drive business outcomes.

Collaborate with Cross-Functional Teams:

Work closely with data scientists, business analysts, data engineers, and IT experts to develop comprehensive data solutions.

Foster a Collaborative Culture:

Encourage information sharing and expertise development, leading technical authority meetings, lunch and learn sessions, and design community events.

Essential Qualifications:

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15+ Years of Experience in Data Analysis and Reporting:

Proven track record of success in data analysis and reporting roles, with a strong understanding of data analytics and science.

5+ Years of Experience in Leadership or Senior Roles:

Demonstrated ability to lead and guide teams, with a strong understanding of technical leadership and team management.

5+ Years of Experience with Cloud Technologies:

Proven experience working with cloud-based technologies, such as ADLS, Databricks, and Delta-Lake.

Advanced Skills in Data Analysis Tools and Languages:

Strong proficiency in data analysis tools and languages, including Conos, PowerBI, SQL, Python, and R.

Experience with Data Representation Tools:

Proven experience working with data representation tools, such as Tableau, Power BI, or similar tools.

Strong Understanding of Cloud Stages:

Experience working with cloud stages, such as AWS, Azure, or Google Cloud, to design and execute adaptable and effective data analysis solutions.

In-Depth Knowledge of Lakehouse Design Standards:

Strong understanding of lakehouse design standards, combining the best of data lakes and data warehouses for efficient and adaptable data management.

High-Level SQL Skills:

Strong proficiency in SQL, with a deep understanding of database design and data modeling.

Experience Managing High-Volume and High-Speed Data Streams:

Proven experience managing high-volume and high-speed data streams, with a strong understanding of data processing and analysis.

Experience in Shaping the Vision for Data Analysis and Reporting:

Demonstrated ability to drive the vision for data analysis and reporting, with a strong understanding of business objectives and technical leadership.

Preferred Qualifications:

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Master's or Ph.D. in Computer Science, Informatics, Data Science, or Related Field:

Advanced degree in a relevant field, with a strong understanding of data analytics and science.

Relevant Industry Certifications:

Industry certifications, such as Certified Data Scientist or Certified Analytics Professional, are a plus.

Experience in Retail, Manufacturing, E-commerce, or Supply Chain:

Proven experience working in retail, manufacturing, e-commerce, or supply chain industries, with a strong understanding of business operations and data analysis.

What We Offer:

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Competitive Salary:

A highly competitive salary, with a range of $160,000 to $230,000.

Comprehensive Benefits Package:

A comprehensive benefits package, including medical, dental, vision, hearing aid, pharmacy, social health, employee assistance, health savings account, dependent care assistance, short-term disability, and long-term disability insurance.

401(k) and Stock Purchase Plan:

A 401(k) plan and stock purchase plan to qualified employees.

Opportunities for Growth and Development:

Opportunities for growth and development, with a strong focus on continuous learning and professional development.

How to Apply:

If you are a highly skilled and experienced Full Stack Data Engineer looking for a new challenge, please submit your application today. We look forward to hearing from you and exploring how you can contribute to our team's success. Apply for this job