... success. Migrate and transform client corporate governance data and documents into Diligent platforms, ensuring accuracy, consistency, and completeness. Run regular data quality checks, validate data against source records, and quickly correct errors to maintain high data integrity. Use advanced Excel functions, databases, and ...
... well-documented code that others can understand and maintain All About You passionate about using data visualisations to tell stories 1–3 years experience in creating data visualisations proficient in R or Python proficient in using code to clean data, transform, and aggregate data familiar with version control concepts and tools ...
Experience : 7+ years of experience in Data Engineering, Data Quality, or Data Governance. 3+ years of experience working on AWS Data Platforms. Strong hands-on expertise in: - Python - SQL - Data Quality Engineering - Data Profiling - Data Validation Frameworks - Experience building AI-powered data quality and governance ...
... production-ready Tableau dashboards. ~ Data Querying (Mandatory): Expert-level command of SQL for data extraction and manipulation. - Proven experience working with data in the Fintech, Banking, or Financial Services sectors. - Soft Skills: Proven ability to engage with non-technical business leaders to understand their data needs ...
... bringing passion and customer focus to the business. Data Engineer (data integration and streaming platforms) Data Engineer with strong experience in event-driven data integration and streaming platforms, ideally with hands-on expertise in Confluent Kafka and CDC technologies. Experience Strong Data Engineering background, including ...
... and acceptance criteria. - Hands-on experience with data validation, reconciliation, source-to-target mapping, UAT, and defect management. - Understanding of data flows, cloud platforms, data repositories, and reporting/visualization layers; experience working with Engineering, Data, Analytics, and Technology teams in Agile ...
... and data quality to ensure accuracy and availability.- Contribute to documentation and adhere to data engineering best practices.- Support the team in various data-related tasks and be eager to learn new technologies and https://jobeax.com/link/b4yK9UFTLnSjLxNr Qualifications:- Bachelor's degree in Computer Science, Information ...
... scientists and provides constructive technical guidance. Experience and Qualifications Master's degree or PhD in Data Science, Statistics, Mathematics, Computer Science or a related field, or a bachelor's degree with significant equivalent experience. Significant experience delivering data science projects from problem definition ...
... application development to join our team. The role involves managing development of FastAPI based applications to run large data modeling, and leveraging the Databricks platform. The ideal candidate will have a robust background in backend development, Data science model basics, and cloud-based solutions to drive data-driven ...
... focus on Java, Microservices and Kafka Java Microservices Back end Developer Java Sprint boot Microservices with expected knowledge of Kafka, Basic knowledge of Database. Experience with TDD and BDD. Must have experience with one of cloud (GCP, AWS or Azure). Also experience with Kubernetes and containers - Hands-on experience ...
... Responsibilities: Design, develop, and maintain scalable ETL/ELT pipelines. Build and optimize data warehouses, data lakes, and data models. Develop highly available data ingestion and processing systems for large datasets. Collaborate with cross-functional teams to deliver data solutions. Ensure data quality, performance, reliability, ...
Project Role: Associate Data Team Lead/Data Team Lead Work Experience: 8+ Years. Work Mode: Hybrid/Homebased Clinical data management, Rave, SSU experience. Shift Timings: 5:00 am -2:00 pm / 2:00 pm – 11:00 pm The shift assignment is purely based on project requirements and the candidate must be open to working in either ...
... orchestration tools (such as Kafka, Redpanda, Airflow, Spark, or Beam) and an understanding of how to run them efficiently. Practical experience leveraging cloud-native data warehouses or lakehouses (such as BigQuery, Snowflake, ClickHouse, or Redshift) for high-performance analytics. Cloud & DevOps Foundations: Solid working knowledge ...
... years of experience as a Data Analyst or Analytics-focused Engineer . Strong proficiency in Python for data analysis. Solid experience with SQL and relational datasets. Experience analyzing ML outputs and evaluation metrics . Ability to work with large, complex datasets and draw reliable insights. Experience writing clean, ...
... affordable healthcare. Build and manage digital analytics datasets and reporting solutions Develop data pipelines and analytical reporting frameworks Support data validation, UAT, process improvements, and analytics initiatives. Experience & Qualification: Python Power BI & Dashboard Development Data Modeling & Data Validation ...
... lifecycle. Design and build scalable backend services, REST APIs, integrations, and reusable software components using Python and, where relevant TypeScript. Develop data ingestion, transformation, service-to-service communication, and automation capabilities that support reliable product experiences. Contribute to AI-enabled features ...
... application development to join our team. The role involves managing development of FastAPI based applications to run large data modeling, and leveraging the Databricks platform. The ideal candidate will have a robust background in backend development, Data science model basics, and cloud-based solutions to drive data-driven ...
... members, and stay updated on the latest data engineering trends. Must-Have Qualifications: Education: Bachelor's or Master's degree in Computer Science, IT, Data Science, Mathematics, or a related field (Recent graduates from batch [Year] are welcome). Python: Solid foundational knowledge of Python programming (data structures, ...
... data ingestion pipelines leveraging Databricks, Airflow, Kafka, and Terraform. Ensure high performance, reliability, and efficiency by optimizing large-scale data pipelines. Develop data processing workflows using Databricks, Delta Lake, and Spark technologies. Maintain and improve the Data Lakehouse, utilizing Unity Catalog ...
... pass an acceptance gate before it is declared complete — you own the evidence behind that. Enabling everyone else The integration and document engineers land data into your platform. Analytics and validation work builds on top of it. Making both easy is part of the job. The Expected Stack The architecture is being finalised ...