Senior/Lead Data Engineer (Databricks) at Exadel Inc (Website)

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Full Time

Start Date

Immediate

Expiry Date

31 Dec, 25

Salary

0.0

Posted On

02 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Databricks, Data Architecture, ETL, ELT, Python, PySpark, SQL, Data Warehousing, Lakehouse Architecture, Power BI, Agile, SCRUM, Data Modeling, Data Governance, Data Quality

Industry

Software Development

Description

Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client The health and fitness software and payment processing provider in the United States, Puerto Rico, Canada, and Mexico. Founded in 1981, they currently work with 7,000+ health clubs. Customer offerings include payment processing and gym management solutions that allow managers to track memberships and schedules and automate payment processing functions. What You’ll Do Support the migration from Synapse to Databricks across multiple data streams Design and implement scalable solutions for: • Initial data load • Data mart and consumption layer • Reporting and Power BI integration Collaborate with product and business teams to understand requirements and deliver data-driven solutions Optimize data pipelines for performance, scalability, and reliability Ensure best practices in data modeling, ETL/ELT processes, and storage optimization Write unit and integration tests to ensure data quality and consistency Diagnose and resolve issues in data pipelines, performance bottlenecks, and integration points Keep up with evolving technologies in the data engineering and cloud ecosystem, recommending improvements to keep the stack up to date What You Bring 8+ years of professional experience in data architecture and cloud-based data platforms Proven expertise in designing and leading large-scale implementations on Databricks Deep knowledge of data warehousing, lakehouse architecture, and consumption layer design Strong background in enterprise data modeling, governance, security, and compliance Ability to define reference architectures and best practices for scalable ETL/ELT pipelines Proficiency in Python, PySpark, and SQL with the ability to guide engineering teams on performance optimization Experience integrating analytics and reporting solutions, including Power BI, into enterprise data platforms Demonstrated ability to review, mentor, and elevate the technical capabilities of engineering teams Experience working in agile teams using SCRUM methodologies Strategic mindset with a focus on scalability, cost optimization, and long-term platform evolution English level Upper-Intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Responsibilities

Support the migration from Synapse to Databricks and design scalable solutions for data processing and reporting. Collaborate with teams to optimize data pipelines and ensure best practices in data modeling and ETL processes.