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 ...
... Hands-on experience with data lineage tools and techniques, including graph databases and metadata management platforms. Knowledge of data governance frameworks, data quality dimensions, and regulatory requirements (e.g., BCBS 239, GDPR) Experience with AI/ML technologies and their application to data management challenges ...
... learning, statistical modeling, and process-mining algorithms to large, multi-source enterprise datasets. - Strong programming proficiency in Python, SQL, and data-modeling techniques for event data. - Experience in process data model design, development, and deployment, including creation of reusable data schemas and pipelines ...
... production-ready code and perform data analysis with Python and SQL Create workflows for model development and apply feature engineering methods Use Azure AI Search to make data and models easier to consume for business needs Coordinate with developers and project managers using GitLab and Jira Refine data pipelines and tune model performance ...
... (dashboards, APIs, ML models) to support digital agronomy and sustainability reporting. - Maintain data quality, document methodologies, and support junior geospatial analysts. - Promote best practices in model development and code quality. - Translate business problems into data science solutions and communicate results to stakeholders. ...
... and modern orchestration — empowering the organization to make reliable, governed, data-driven decisions. Data Platform Architecture: Design and own end-to-end data pipeline architecture — ETL/ELT, orchestration, and data modeling — across cloud-native platforms (Azure Databricks, Azure Data Factory, and/or Snowflake). Lakehouse ...
... analytics environment with proven analytics and insights expertise at Lead Analyst level or equivalent- Technical proficiency : Strong expertise in BigQuery SQL and data visualisation tools- Leadership experience : Proven experience leading teams of analysts and managing analytical deliverables- People management : Experience ...
... consistency, completeness, and integrity of data across Oracle-based systems through validation and quality checks.- Work with multiple IT roles including Data Analysts, Solution Architects, and Information Architects to embed the use of data models within both project and strategic activities.- Work with business data governance ...
... workflows, and structured output pipelines for LLM applications. Fine-tune, evaluate, and optimize LLM-powered applications for accuracy, latency, and cost. Implement data preprocessing, feature engineering, and ML model training workflows. Work with structured and unstructured datasets to solve business problems. Collaborate with ...
... hands-on professional experience Education: BE/B.Tech/ME/M.Tech/MCA/MSc IT Primary Skills (must have): Strong Azure or AWS knowledge Strong working knowledge on Data Science, Artificial Intelligence, Machine Learning Secondary Skills (good to have): SQL, Python Professional Attributes: Strong analytical and problem-solving ...
... analytics. The successful candidate will work extensively with Python and PySpark, use R where appropriate, and collaborate with product managers, industry analysts, data scientists and technology partners. The role also contributes to cloud and DevOps activities across AWS, Docker and Terraform when needed. A key part ...
... improve stewardship productivity, reduce data defects, and enhance reporting confidence. technologies, SAP MDG capabilities, Syniti functionality, AI-enabled data quality, and industry best practices. Team building and mentorship: Build and mentor a high-performing MDM team including data stewards, analysts, functional ...
... proficiency in SQL and Python for data processing and pipeline development. Data Platforms: Hands-on experience with Snowflake, dbt, and modern cloud data warehouses. Data Modelling: Deep experience with dbt and modern data modelling practices. Data Platforms: Hands-on experience working with Snowflake or comparable cloud data warehouses ...
... Measurement Team that specializes in the ingestion, transformation, and storage of large-scale social and broadcast data. Working under the guidance of an experienced Data Engineers and Architects, you will gain hands-on experience designing and maintaining scalable, efficient data pipelines that support enterprise web applications, ...
... best practices. Present findings, recommendations, and AI roadmaps to leadership teams. Provide technical guidance and mentoring to junior data scientists and analysts. Collaborate with global teams and external partners to deliver data-driven solutions. Advanced knowledge of Python, SQL, and modern data science libraries. ...
... comprehensive benefits package includes health insurance, wellness programs, learning & development opportunities, and more. Job Title: Data Scientist 2 Understand data landscape Perform ad-hoc analysis and present results in a clear manner Work on the full lifecycle of machine learning development including sourcing, dataset ...
Role Purpose This role is responsible for driving enterprise-wide data engineering strategy. It ensures the design, implementation, and continuous improvement of data pipelines, scalable and reusable frameworks, and implement data governance and data quality engines. The position enables trusted, governed data across systems, ...
... practices including version control, testing, and CI/CD - Participate in code reviews and provide constructive feedback to team members - Troubleshoot and resolve data pipeline issues in production environments Collaboration & Knowledge Sharing - Work closely with data architects, analysts, and business stakeholders - Collaborate ...
... distributed architectures, and modern data engineering https://jobeax.com/link/TtkK7BHPbancvnFq Responsibilities:- Design, develop, and maintain scalable ETL/ELT data pipelines.- Build and manage distributed and event-driven architectures for large-scale data processing.- Develop backend services and data infrastructure using ...
... using Python and PySpark to ingest data from files, APIs, RDBMS, NoSQL, and message queues into AWS data stores Develop and optimize PySpark jobs for large-scale data processing, transformation, and aggregation on AWS EMR or Databricks Build and manage AWS-native data workflows using S3, Glue, Lambda, Redshift, and Step Functions; ...