... SLA responsibility in an ML/AI data operations environment - Knowledge of databases (SQL, MySQL) and Advanced Excel experience working with and analyzing large datasets to drive business improvements - Familiarity with ML data annotation workflows, labeling tools, or AI/ML program operations - Experience working in geographically ...
... 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 ...
... (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. ...
... 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 ...
... 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 ...
... for leading both the technical and functional aspects of enterprise Master Data Management, including master data strategy, governance, standards, stewardship, data quality, workflow design, integration, migration readiness, and ongoing operations. The role will act as the single point of contact (SPOC) for master data across ...
... transformations, and performance tuning. - Good experience with Python for data processing, automation, and Lambda development. - Strong understanding of data warehousing, data modeling, ETL/ELT, and data lake concepts. - Experience building and supporting production data pipelines. - Experience troubleshooting data and pipeline performance ...
... 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 ...
Senior Data Engineer – Graph Database & Data Intelligence Position: Senior Data Engineer Experience Required: 6+ Years Location: Remote Employment Type: Contract We are seeking a highly skilled Senior Data Engineer with expertise in Graph Databases, Data Modeling, and modern backend frameworks. The ideal candidate should ...
... audit-sensitive environments such as: - Healthcare claims - Finance back-office operations - Legal operations - Other compliance-sensitive data environments Core Skills - Data Entry - Data Validation - Data Quality Assurance - Error Detection - Data Reconciliation - Accuracy Control - Data Integrity - Format Reconciliation - Dataset ...
... high-volume data applications. Who Should Apply This role is suited to data engineers who have practical experience working with large-scale datasets and distributed data systems. You should be comfortable moving between pipeline development, database optimization, data processing, infrastructure reliability, and data governance. ...
... high-volume data applications. Who Should Apply This role is suited to data engineers who have practical experience working with large-scale datasets and distributed data systems. You should be comfortable moving between pipeline development, database optimization, data processing, infrastructure reliability, and data governance. ...
... our SaaS and insurance operations. You will work closely with lead architects to implement scalable solutions and serve as a subject matter expert in SQL and database performance. What You Will Do As A Data Warehouse Engineer Build and monitor robust ETL/ELT pipelines using BigQuery, Dataflow, and Cloud Composer. Expert ...
... processes for batch and streaming analytics requirements. Optimize and troubleshoot distributed systems for ingestion, storage, and processing. Collaborate with data engineers, analysts, and platform engineers to align solutions with business needs. Ensure data security, integrity, and compliance throughout the infrastructure. ...
Data Engineer III/ IV - IN (Operation/ Supports) Work Location - Remote Work From Home Shift: Rotation Shifts (24/7) Experience: 7-12 years The Data engineer is responsible for managing and operating upon Databricks, Dbt, SSRS, SSIS, AWS DWS, AWS APP Flow, PowerBI/Tableau. The engineer will work closely with the customer ...
... data models in Snowflake for analytics and visualization. Ensure data accuracy, performance optimization, and visualization best practices. Work closely with data engineering to ensure smooth data integration and pipeline readiness. Troubleshoot issues related to data, performance, or visualization logic. Overall 5+ years ...
... manage databases and data warehouses and optimise database performance and storage across multipul platforms, e.g. Snowflake, PostgreSQL RDS & Aurora. Ensure data quality, integrity, and reliability, whilst adhering to data security best practices. Work closely with data analysts, and other stakeholders to understand data ...
... modelers and analysts to deliver analytics-ready datasets Support downstream reporting and dashboarding use cases What we’re looking for Strong experience as a Data Engineer in Azure environments Hands-on with tools such as Azure Data Factory, Azure Databricks, Synapse or similar Solid SQL and data transformation experience ...
... tracing. Strong written and verbal communication skills, with the ability to collaborate effectively across time zones with onshore data architects, business analysts, and platform engineering teams. Demonstrated willingness to learn new technologies and expand responsibilities beyond traditional data engineering (e.g., ...