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Mastercard Philippines is hiring a Senior Data Engineer to design and maintain large-scale data platforms, working across teams to validate, optimize, and productionize data pipelines. The core stack is Spark, Kafka, and NiFi, with emphasis on distributed streaming architectures and cloud-native data processing.
Designs and builds data platform architecture at Accenture Philippines, with hands-on development of ETL/ELT pipelines using AWS Glue, Python, PySpark and related AWS data services. Day to day includes automation, performance tuning, CI/CD support, and collaborating with Integration and Data Architects on data models and system integration.
A hands-on staff-level platform engineer who owns and operates a billion-row shared data platform, designing and running foundational systems for product and engineering teams. Core stack includes open-lakehouse formats (Iceberg/Delta/Hudi), batch and streaming ingestion, and orchestration on Kubernetes.
Data engineer acting as a subject-matter expert who builds and optimizes Databricks data pipelines, monitors and fixes data quality issues, and documents workflows while guiding team decisions. Core stack: Databricks, Python, ETL/integration tools, cloud data services, and data warehousing.
A senior hands-on engineer who architects, builds, and optimizes data pipelines and warehouse/lake infrastructure on Microsoft Azure (Data Factory, Synapse, Fabric) for external clients, while enforcing governance and CI/CD best practices and mentoring junior data engineers.
A data engineer who designs, builds, and maintains data marts, ETL pipelines, and big-data systems, ensuring their reliability, scalability, and performance with quality monitoring and alerting. Core stack is Scala/PySpark, Spark, Hadoop, Kafka, Impala, Azure Databricks, and related cloud data tools.
Mid-level data engineer owning slices of a data platform end-to-end: building and operating batch and streaming pipelines from ingestion to warehouse and data products using SQL, Python, Airflow, Kafka/Flink, dbt, Terraform, and GCP. The role also champions AI-assisted engineering (Claude Code) and builds GenAI-powered internal data tools like text-to-SQL and automated data quality.
Lead end-to-end Snowflake data solutions at Accenture Philippines: build scalable Snowflake pipelines, ensure data quality, migrate data via ELT, tune performance, and enforce governance with RBAC and masking policies while collaborating with business teams.
Design, build, and maintain scalable data platform infrastructure and ETL/ELT pipelines that power analytics, AI/ML, and BI for a Gartner-recognized AI supply chain scaleup. Core focus areas are distributed data systems, cloud infrastructure, and large-scale batch and real-time data processing.
Associate-level data engineer on BlackRock's Aladdin Data team who designs, builds, tests, and maintains Enterprise Data Platform frameworks — automating pipelines for acquisition, ingestion, processing, orchestration, and data quality using Airflow, Python, Snowflake, dbt, and Azure, with L2/L3 support in a hybrid, office-first setup.
A data engineer at Accenture Philippines who designs, builds, and maintains scalable ETL/ELT data pipelines on Databricks (Delta Lake, Auto Loader, DLT, Unity Catalog) using Python and PySpark on a cloud platform (AWS/GCP/Azure), with BI integration, GenAI-ready datasets, and CI/CD deployment.
Senior data engineer to help Novo Nordisk Engineering (NNE) scale its Azure-based data platform, working primarily in Microsoft Fabric. Day to day: maintaining platform infrastructure, designing ETL/ELT pipelines and data models, driving governance, data quality, CI/CD and engineering standards, and mentoring colleagues.
Senior Snowflake data engineer role at Accenture in Cebu, Philippines: the person designs, builds, and leads end-to-end Snowflake data solutions — creating ETL/ELT pipelines, tuning performance, setting up governance (RBAC, masking), and enabling GenAI via Snowflake Cortex AI. Core stack: Snowflake, SQL, Snowpark, and a major cloud (AWS, Azure, or GCP).
Design, develop, and maintain scalable data pipelines using Azure services for global projects at Tech Mahindra, collaborating with data scientists, analysts, and architects. Requires 3+ years of experience with strong Azure and SQL skills, working in a hybrid setup from Makati City, Philippines.
A senior data engineer on EY's GDS Data Engineering team builds cloud data ingestion and processing pipelines and supports BI/analytics solutions, working alongside EY Consulting practices globally. Core tech includes Azure Data Factory, Synapse/Fabric, Databricks, Snowflake, Python/PySpark/SQL, and BI tools like Power BI and Tableau.
Senior Data Engineer who designs, builds, and maintains scalable, reliable data processing systems and pipelines, collaborating with data scientists and analysts and mentoring junior engineers. Works with Python/Scala/Java, Spark, Hadoop, Kafka, SQL/NoSQL databases, cloud platforms (AWS, Azure, GCP), and orchestration tools like Airflow.
Data Engineer on Dow's Environment, Health, Safety and Sustainability IT team, focused on ingesting, persisting, and curating data across Azure-based enterprise data platforms. Day to day involves building pipelines with Azure Data Factory and Databricks and collaborating with data scientists on scalable data architectures.
Design, build, and optimize data pipelines and architectures, handling data integration and transformation while ensuring the scalability and reliability of data infrastructure. Core skills: ETL, data modeling, SQL, cloud platforms, and big data technologies; 3-4 years of experience required.
A junior data platform engineer role supporting and maintaining big data environments — Apache Spark clusters, Airflow, Hive/Hadoop, and JupyterHub — while writing Python automation and ETL scripts and troubleshooting Spark jobs under senior engineers' guidance.
V2 Solutions seeks a Data Engineer to design, build, and optimize data pipelines and architectures, ensuring data quality and performance for analytics and data science initiatives. Day-to-day work centers on ETL, data modeling, SQL, and cloud platforms, with big data and distributed processing as a plus.
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