... during your interview. Position Title – Senior Data Engineer The Senior Data Engineer will lead the design, development, and optimization of enterprise-scale data pipelines and integration solutions. This role requires deep expertise in data engineering principles, strong knowledge of relational databases, and experience ...
... Support data governance, cataloguing, lineage, and metadata management practices where required. Work with Linux/Unix environments and efficiently process large datasets. WHAT MAKES YOU A GREAT FIT - 3+ years of professional experience in Data Engineering, Big Data, Analytics Engineering, or a related field. - Strong hands-on ...
Job Description – Data Engineer Experience: 5–7 Years Role: Sr. Data Engineer Department: Data Engineering / Product Engineering Role Overview We are looking for an experienced Data Engineer with 5–7 years of hands-on experience in ETL/ELT, database engineering, Big Data processing, and complex bi-directional data integrations ...
... orchestrate datasets. Perform routine data monitoring, quality checks, and troubleshooting to maintain data integrity and workflow performance. Collaborate with data analysts, data scientists, and senior engineers to deliver data solutions. Document workflows, dataset schemas, and data engineering best practices. Required ...
... Engineer Professional Additional Certifications (Preferred) - Databricks Certified Associate Developer for Apache Spark - Cloud platform certifications (Azure Data Engineer Associate, AWS Certified Data Analytics, or Google Cloud Professional Data Engineer) - Relevant data engineering or big data certifications Soft Skills ...
... Product engineering team to influence designs with data, AI and analytics use cases in mind - In depth experience in System design involving large Petabytes of data with Databricks Lakehouse - Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context) - AWS, GCP, ...
... Science, Engineering, or a related field. - Over 5 years of software development experience, with at least 2 years in a technical leadership role overseeing data engineering or data platform teams. - Strong proficiency in big data technologies, including Apache Spark/PySpark, Apache Airflow and Apache Kafka. - Experience ...
Big Data Processing: Design and manage scalable data pipelines to process massive datasets efficiently for model training and inference. Build, train, and fine-tune complex neural networks across text, audio, and visual modalities. Cloud Deployment: Architect and deploy models to cloud environments, leveraging distributed ...
... enterprise, recognized as a global Microsoft and Databricks https://jobeax.com/link/z5IScpoZA6T2iqD7 bridge enterprise challenges with modern intelligence across Big Data, Cloud Infrastructure, Data Engineering, and Applied Artificial https://jobeax.com/link/Z4S3vFYKsGGU38on Overview :We are seeking an experienced Senior Data Scientist ...
... enterprise, recognized as a global Microsoft and Databricks https://jobeax.com/link/z5IScpoZA6T2iqD7 bridge enterprise challenges with modern intelligence across Big Data, Cloud Infrastructure, Data Engineering, and Applied Artificial https://jobeax.com/link/Z4S3vFYKsGGU38on Overview :We are seeking an experienced Senior Data Scientist ...
... cost.- Big-data and pipeline fluency: Advanced SQL plus distributed processing for large spatial workloads (Spark or Dask), and building reliable, repeatable data pipelines.- Productionizing models: Experience turning models into deployable, real-time APIs in collaboration with engineering - clean, tested, well-documented ...
... Experience with data quality tooling (SODA, Collibra, or similar) Exposure to cloud platforms (Azure, AWS, or GCP) Experience in a regulated or enterprise-scale data environment Prior experience mentoring or leading a small pod of engineers EXPERIENCE - 8+ years in data engineering, with at least 4+ years focused on Snowflake ...
... Azure Data Factory, Azure Data Lake, Microsoft Fabric, Logic Apps,Power BI, GitHub, and Data Modeling. Required Skills: - 10+ years of Software Engineering / Data Engineering experience. - Strong SQL Server and T-SQL expertise. - Strong experience working in the Azure environment. - Hands-on experience with Azure Data Factory. ...
... checks Contribute to and help shape company-wide data governance standards Collaborate with analytics, BI, and business teams to deliver trusted, well-modeled data 5–7 years of hands-on data engineering experience - Proven production data engineering experience at scale - Strong Python and SQL skills - Deep analytical warehouse ...
... production issues, work with Databricks to open incident tickets/case and follow up to close the issue and ensure long term fixes - Additional knowledge of other Databricks key features, like Genie, Apps, Models creations etc Required Qualifications: - Bachelor's degree in computer science, Information Technology, Engineering, ...
... Engineer will own the end-to-end operationalisation of machine learning, large language model (LLM), and agentic AI workloads on the Bajaj Finance Enterprise Data Platform — a 5PB+ medallion lakehouse built on Azure Databricks and Unity Catalog. This role sits at the intersection of data engineering, model lifecycle management, ...
Job Summary We are looking for a skilled Data Engineer with a strong background in building scalable, high-performance data pipelines on Google Cloud Platform (GCP) . The ideal candidate will have hands-on experience with BigQuery , Airflow , and cloud-based ETL workflows , along with solid programming expertise in Java ...
... https://jobeax.com/link/fYGlpInxuIv5PeS1 & Skills :- 4 - 7 years in data engineering: SQL, Python, ETL/ELT orchestration.- Cloud data platform experience (Azure preferred): pipelines, storage, APIs.- Strong understanding of data lake and data architecture.- Data modelling for analytics (star schema) and data quality frameworks. (ref:hirist.tech)
... in driving value for our customers by building data solutions. You'll be carrying out data engineering tasks to build, maintain, test and optimise a scalable data architecture, as well as carrying out data extractions, transforming data to make it usable to data analysts and scientists, and loading data into data platforms. ...