科技職缺
職缺列表
Data Engineer I
Build and maintain data pipelines, models, and workflows for analytics at DHL Supply Chain, ensuring data governance and quality across integrated systems in a remote role.
Data Engineer Lead
Lead data engineering efforts building ETL/ELT pipelines and scalable cloud-native data platforms while driving architecture decisions, mentoring engineers, and implementing data governance, quality, and lineage practices.
Senior Data Engineer (MS Fabric Experience)
Senior data engineer designing and building cloud-native data platforms on Microsoft Fabric — building end-to-end ETL pipelines, lakehouse/warehouse models, semantic models, and Power BI reports within agile teams.
Data Platform Engineer
Data Platform Engineer at Harman International building data lakehouse architectures, ingestion pipelines, and data APIs to curate datasets for AI/ML, with responsibility for governance, data quality, and pipeline reliability.
Operations Support - Business & Data Analytics
Operations support role in business and data analytics: migrate Oracle data sources to Snowflake, build Tableau and Alteryx dashboards, develop custom data models and algorithms, and create executive visualizations to surface business opportunities.
Data Analyst
Data Analyst role analyzing workforce data, building and maintaining reports and dashboards, automating recurring reporting, developing reusable data models, and ensuring GDPR-compliant data quality and governance across HR and business systems.
Junior Data Engineer
Junior data engineer at DHL building data pipelines, developing Power BI reports and data models, onboarding new data sources, and supporting data governance and quality initiatives.
Data Engineering Lead (GCP, Bigquery, ETL, Prompt Engineering) Associate Director
Lead a data engineering squad at HSBC building and operating batch/streaming data pipelines on GCP/BigQuery, owning data platform architecture, governance, lineage, FinOps, CI/CD, monitoring, and ETL/ELT delivery while coaching engineers.
Senior Manager, Manufacturing AI & Analytics
- Align capacity sequencing and dependencies - Assess solution feasibility data readiness and integration risk - Capture implementation learning for future deployments - Connect delivery to operational and financial…
Analyst, Market Insights & Analytics
Creates charts, dashboards, and data-driven insights while maintaining KPI trackers, data dictionaries, and standardized reporting on market, competitive, and category performance at Ulta Beauty.
Data Engineer
Data Engineer at Numentica working remotely from Saidapet (Chennai, India) to automate data engineering workflows, build data infrastructure, design ETL pipelines, implement data governance and testing, and deploy cloud data solutions.
Data Architect, AI and Data Practice
Data architect role at a consulting firm, designing data warehouse/lakehouse solutions and Power BI semantic models, developing ELT pipelines, implementing governance with Microsoft Purview, and supporting AI-agent-ready semantic layers in Microsoft Fabric.
Senior Technical Consultant - Data Architect
Senior Technical Consultant / Data Architect at CACI Ltd advising on AI/ML and advanced analytics, designing Databricks Lakehouse and Snowflake environments, and leading cloud data platform migrations for enterprise clients.
Senior Data Engineer (French Speaker) | BPCE-SI
Senior data engineer designing data integration solutions and Power BI dashboards using PL/SQL for a French banking group (BPCE), maintaining and optimizing ETL pipelines, and evolving data warehouse models in a French-speaking environment.
Salesforce Developer – Agentforce & AI Solutions
Design and develop AI-powered Salesforce solutions using Agentforce, Apex, LWC, Flows, and SOQL APIs. Day-to-day work focuses on building customer service and membership workflows, integrating with Data Cloud and external platforms, and running unit, integration, and UAT cycles.
Data Quality Analyst - Senior 1
Senior data quality analyst at Cummins owning enterprise data quality: cataloguing business attributes, developing DQ rules and KPIs, profiling and validating data, leading root-cause analysis, and embedding quality practices across the data lifecycle.