... Docker, Cloud-Native Infrastructure, CI/CD pipelines. Industry Context: Data engineering experience in Banking Risk, Retail Products, Cards, Mortgage, Deposits, or Wealth Management. Assumed Requirements / Certifications: Databricks Certified Data Engineer, AWS Certified Data Analytics, or Azure Data Engineer Associate.
... workflows, dose analysis, and program management for radiation safety professionals. We are looking for a seasoned Data Engineer to take a lead role in shaping the data foundation across Landauer's growing portfolio of products. You will set the standards for how data is modeled, moved, and governed — owning the full data lifecycle ...
... recurring insight packs and basic statistical summaries under supervision.- Run data quality checks and validate metrics.- Support test cases, documentation and data validation for dashboard https://jobeax.com/link/uZNeF9ElGyYiAC23 We Expect From You :- Build strong SQL and data-hygiene habits early; accuracy matters more ...
... of truth. Develops and operationalizes data pipelines to bring data into Costco’s GCP landscape for the delivery of certified data sets Works in tandem with Data Architects, Data Stewards, and Data Quality Engineers to design data pipelines and recommends ongoing optimization of data storage, data ingestion, data quality ...
... activities and site communications. Collaborate with the project team to address issues, resolve discrepancies, and ensure trial milestones are met. Support data management activities by ensuring timely and accurate data collection and entry. Participate in audits and inspections as required, providing necessary documentation ...
... Data Engineer will design, build, and maintain scalable data pipelines and solutions, ensuring high performance and reliability across COSMOS DB and related data platforms. Daily responsibilities include modeling and structuring data, implementing ETL processes, optimizing data storage and retrieval, and collaborating ...
Key responsibilities :Data Architecture & Platform Build :- Design and implement modern data architecture (Data Lake, Data Warehouse, Lakehouse)- Enable self-service analytics and reporting platforms- Lead implementation of BI tools and dashboards- Partner with business teams to define KPIs, metrics, and insights frameworks- ...
... solutions in Client Data Product Management . As a Data Product Manager within our dynamic team , you will be responsible for scaling the CDM(client data management) data product, strengthening operating models, and driving operational excellence through data-driven execution. Drive product development for the CDM data product ...
... hands-on experience in data science.- Strong proficiency in Python and libraries such as NumPy, pandas, scikit-learn, TensorFlow/PyTorch.- Expertise in SQL for data extraction, transformation, and analysis.- Proven experience with PySpark or distributed data processing frameworks.- Deep understanding of machine learning and ...
... strategies based on statistical analyses and insights from historical datasets. Show how the current trading performance can be enhanced with use of more granular data, more graduated levers, and how simple, low risk decisions can be automated. Collaborate with developers and commercial leaders to integrate data-driven improvements ...
... coaching, performance management, career development, and team engagement. Data Architecture: Deep understanding of modern data architecture patterns including Data Lakes, Data Warehouses, Lakehouses, and Data Mesh, combined with experience designing and delivering cloud-based data platforms. Cloud and Data Engineering: Strong ...
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 ...
... Point - Ability to prioritize tasks, manage multiple responsibilities and ensure deadlines are met without compromising on quality - Basic data handling and Data interpretation skills - Should be comfortable with 24x7 rotational shifts - Ability to pull data from numerous databases (using Excel and other data management ...
... Data Factory or equivalent. Data Handling: Expertise in data engineering, including data cleaning, transformation, and preparation for analysis. Knowledge of data modelling, database design, and data architecture principles. Data Quality: Proven experience in data quality management, including data cleansing, validation, ...
Role Overview :The Senior Data Scientist, Product Analytics is a hands-on technical contributor and task manager within a cross-functional product team. This role sits at the intersection of deep technical execution and emerging AI https://jobeax.com/link/f9LyLs7glaUomOJP And Qualifications :- 5 - 7 years of experience ...
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 ...
Role Overview We are looking for a Senior Data Analyst to work on a broad range of data analytics, data visualization, and business intelligence initiatives across multiple industries. The role requires strong analytical skills, frequent client interaction, and the ability to translate business problems into effective analytical ...
... 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 ...
... factual accuracy, or comparing responses — when projects are available. While each project involves unique tasks, contributors may: - Carefully review provided data (text, images, or videos); - Label or classify content based on project guidelines; - Identify and flag factually incorrect, sensitive, inappropriate, or unclear ...