--- title: 'Senior Data Engineer - Databricks at ShyftLabs' canonical: 'https://feeny.ai/job/senior-data-engineer-databricks-shyftlabs-coimbatore-6qjdqbmk31yr' type: 'job' last_seen: '2026-11-10' --- # Senior Data Engineer - Databricks at ShyftLabs - **Company:** ShyftLabs - **Location:** Coimbatore, India - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-11-10 - **Last confirmed live:** 2026-11-10 - **Apply:** https://jobs.lever.co/shyftlabs/9cb29ad5-f4db-4404-877c-1e420e80374e ## Job description Position Overview We are looking for a Data Engineer with hands-on experience in building scalable data pipelines and data engineering solutions on the Databricks Lakehouse Platform. The ideal candidate should have strong expertise in Python, PySpark, SQL, Databricks, AWS, and REST API integrations for data ingestion, managing large volumes of data, and data export ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation. Job Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, PySpark, Python, and SQL. Work on Databricks infrastructure, including workspace configuration, clusters, compute resources, access controls, and performance optimization. Apply Data Governance principles, including data quality, data lineage, metadata management, data cataloging, and access controls. Work with Unity Catalog to manage data permissions, governance policies, and data assets. Develop and manage Delta Lake tables using Medallion Architecture (Bronze, Silver, and Gold). Integrate data from multiple sources, including databases, Amazon S3, files, and REST APIs. Create, schedule, monitor, and optimize Databricks Jobs and Workflows. Implement data validation, error handling, logging, monitoring, and data quality checks. Optimize Spark workloads, SQL queries, and data processing pipelines for performance and scalability. Support data discovery, metadata documentation, and governance standards across data platforms. Collaborate with cross-functional teams to ensure data accuracy, consistency, security, and compliance. Troubleshoot data pipeline and infrastructure issues and recommend improvements to platform reliability. Contribute to enterprise data management and governance best practices. Basic Qualification: 7+ years of overall experience in Data Engineering or a related data technology role. Minimum 5 years of hands-on Databricks experience, including data engineering and/or Databricks infrastructure. Mandatory understanding of Data Governance concepts, including data quality, metadata management, data lineage, data cataloging, data ownership, and access controls. Practical knowledge of data governance principles and their application in data platforms. Understanding of data governance frameworks, policies, standards, and data management best practices. Experience or knowledge of implementing data quality checks, data lineage tracking, metadata documentation, and governed data access. Strong expertise in Python, PySpark, and Advanced SQL. Hands-on experience with the Databricks Lakehouse Platform, Delta Lake, Unity Catalog, Workflows, Jobs, Clusters, and Notebooks. Experience developing ETL/ELT pipelines, data transformations, batch processing, and incremental data loading. Good understanding of data warehousing and data modeling concepts. Knowledge of data security, access management, and governance practices within data platforms. Experience with Spark performance tuning, partitioning, file optimization, and query optimization. Familiarity with Git, CI/CD practices, and production deployment processes. Strong analytical, problem-solving, and communication skills. We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources. ## About ShyftLabs ## Company Overview - **One-liner**: ShyftLabs is a data and AI consulting firm that builds enterprise-grade intelligent systems to help Fortune 500 companies, retailers, health organizations, and public agencies turn data into measurable business outcomes. - **Entity Type**: Private (Bootstrapped) - **Headquarters**: Toronto, Ontario, Canada - **Founded**: 2018 - **Founders**: Brian Würtz Leth (Co-Founder, COO) – additional co-founders are not publicly listed. ## Core Business - **Primary industries**: Data & AI consulting, digital transformation, enterprise technology services. - **Target customers**: B2B, large enterprises (Fortune 500), government agencies, healthcare organizations. - **Mission or purpose statement**: “Move from pain points to measurable outcomes, fast.” They aim to make data actionable and power real-time decisions with privacy-first, responsible AI systems. ## Products & Services - **Enterprise AI & Data Consulting**: Custom AI solutions, machine learning models, and data infrastructure designed for trusted enterprise deployment. - **Digital Transformation Services**: Modernization of legacy systems, cloud migration, and scalable AI-ready platforms. - **Data Infrastructure & Governance**: Building governed data pipelines, privacy-first architecture, and secure integrations. - **Responsible AI Controls**: Governance frameworks, bias detection, and compliance-focused AI deployment. ## Market Standing - **Valuation/Market Cap**: Not disclosed (privately held). - **Key Metric**: Claims to have unlocked over $2B in client value (as stated on their website) and $500M+ in measurable value for clients. - **Notable Investors/Partners**: No public investors listed. Partners include major retailers, health organizations, and public agencies (specific names not disclosed). - **Growth Signals**: - Headcount: ~177 employees (LinkedIn) with +1.4% monthly growth; website states 250+ experts. - Active job postings: 30+ (Lever) with 22 roles posted in the last 90 days. - Offices in Toronto, New York, Dubai, and Noida (India), with distributed teams across 6 countries. - 54% of employees in technical roles, indicating strong engineering focus. ## Competitive Advantages - **Privacy-first architecture** and **governed data infrastructure** tailored for enterprise compliance. - **Multi-geography delivery** (North America, Europe, Middle East, India) enabling 24/7 support and diverse talent pools. - **Track record with Fortune 500 clients** and proven ability to deliver measurable ROI (over $500M client value). - **Full-stack AI expertise** spanning data engineering, machine learning, and responsible AI governance. ## Strategic Focus - Scaling AI systems that power real-time decisions across critical industries (retail, healthcare, government). - Modernizing legacy infrastructure for enterprises moving to AI-ready platforms. - Expanding their presence in commerce media (e.g., Carter partnership) and deepening client relationships through account management. - Growth in autonomous AI agents and privacy-first solutions. ## Why Work Here - **Culture & Ratings**: 4.2/5 on Glassdoor (60 reviews) with Work-Life Balance 4.3, Compensation 4.2, Culture 4.2. - **Benefits**: 100% coverage for health, dental, and vision insurance for employees and dependents from day one. - **Work Environment**: Hybrid policy in Toronto (minimum 4 in-office days per week); other offices vary. Fast-paced, product-focused, and collaborative. - **Growth Opportunities**: Continuous learning, influence over strategic direction, and opportunities to build AI systems used by Fortune 500 companies. - **Diversity & Inclusion**: Equal opportunity employer committed to creating a safe, diverse, and inclusive environment. ## Sources 1. [shyftlabs.io](https://shyftlabs.io/about-us) 2. [LinkedIn](https://linkedin.com/company/shyftlabsio) 3. [Indeed](https://ca.indeed.com/cmp/Shyftlabs/jobs) 4. [GetClera](https://www.getclera.com/companies/shyftlabsio) 5. 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