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Job Description: Job Description: Data Engineer – Databricks & Microsoft Fabric Location : Chennai, India Experience : 6 to 8 years Role Summary We are looking for an experienced Data Engineer with strong hands-on…
Grade: B Job Title: Principal Data Engineer Team: Clara Technology & Solutions Locations: UK Capability: Audit Service line: Audit Central Contract type: Permanent Summary of role purpose: The Principal Data…
Join Us At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect…
Job Summary At Tetra Pak we commit to making food safe and available, everywhere; and we protect what's good – protecting food, protecting people, and protecting the planet. By doing so we touch millions of…
We improve lives The IDB Group is a community of diverse, versatile, and passionate people who come together on a journey to improve lives in Latin America and the Caribbean. Our people find purpose and do what they…
Leads enterprise data governance programs, consulting, and Databricks practice development for a consulting firm, designing frameworks, policies, and client solutions for data stewardship, quality, and metadata management.
Designs end-to-end data architectures for financial clients, mapping flows from source to consumption and integrating systems, platforms, and APIs into scalable solutions.
Senior Software Engineer building tools and frameworks for Apple's AI & Data Platforms, including data processing, ML model hubs, and BI integrations using Java/Python, microservices, and cloud platforms.
Senior Data Engineer designing and evolving ETL/ELT processes, implementing data ingestion/transformations in Data Lake/Warehouse/Lakehouse, ensuring data quality, and acting as technical lead. Core technologies: Databricks, Python, SQL, Spark.
Designs and optimizes scalable, secure data platforms for clinical research analytics, AI/ML, and regulatory compliance using cloud-native tools and distributed systems.
Builds and maintains high-impact data pipelines and services in Python, Spark, and AWS to turn raw data into actionable intelligence for national security missions in McLean, VA.
At Emirates Group our Analytics Centre of Excellence ACoE is a centralized unit that provides data and analytics support to Emirates Group businesses This allows our businesses to make better decisions by using data…
The Senior Data Engineer builds and maintains scalable data pipelines and reliable storage systems using Snowflake, Java, and Python. This role involves leading technical implementation, mentoring team members, and ensuring data governance and quality standards.
Senior Data Engineer building reliable data systems for collection, cleaning, storage, and delivery to dashboards/reports; leads others in implementing target architecture into production, using Snowflake, Boomi, and Talend.
Build data governance infrastructure at a fintech company, writing Python/Terraform to automate quality checks, trust scorecards, and compliance workflows while partnering with engineering and compliance teams.
Leads Michels Corporation’s enterprise data strategy, defining and prioritizing data products to enable self-service analytics, reporting, and AI across the organization’s operations. Focuses on cloud-based data platforms and governance to drive business decisions.
Lead a cross-functional data engineering team designing and operating scalable ETL/ELT pipelines, managing cloud data platforms (Snowflake, Azure/GCP), and establishing engineering best practices including CI/CD and data governance.
Designs and delivers data-driven decision-support tools for federal public safety clients, combining SQL, Python, and Power BI to build dashboards, analyze complex datasets, and mentor junior analysts.
Builds and maintains data dashboards/reports for a federal client, using SQL, Python, and Power BI to analyze structured data and support decision-making in public safety operations.
Design and implement data governance processes on GCP—including data catalog development, metadata management, data lineage, and data quality frameworks—as part of migrating analytical environments to Google Cloud for a digital services organization.
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