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EERNI
Mandaluyong, Philippines4 months ago
Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.
Minimum 8 years of professional data engineering experience, including hands-on design and delivery of enterprise-scale data pipelines, data platforms, ETL/ELT processes, and analytics-ready datasets.
Senior-level hands-on experience with Azure and Azure Databricks is required. Strong experience developing data engineering solutions using Databricks, PySpark, Spark SQL, Delta Lake, and SQL.
Strong understanding of cloud-native data engineering patterns, including scalable ingestion, transformation, orchestration, monitoring, performance tuning, and production support.
Experience building and maintaining data pipelines that process large volumes of structured, semi structured, and unstructured data from multiple source systems.
Strong experience with data modeling, data marts, curated data layers, and business-facing datasets for reporting, analytics, and operational consumption.
Strong ability to clarify requirements directly with stakeholders and translate business rules, data definitions, and process needs into technical implementation details.
Experience with source-to-target mapping, data profiling, data validation, reconciliation, and data quality management.
Experience with job orchestration and scheduling tools such as Azure Data Factory, Databricks Workflows, Airflow, or similar technologies.
Strong understanding of data governance, access control, metadata, lineage, security, and compliance considerations in a cloud data environment.
Experience with performance tuning and optimization of Spark jobs, Databricks clusters, SQL queries, and Delta tables.
Strong troubleshooting, problem-solving, and root-cause analysis skills in production data environments.
Strong communication skills, with the ability to explain technical concepts, risks, dependencies, and delivery options to business and technology stakeholders.
Ability to work independently with minimal supervision while collaborating effectively in cross-functional delivery teams.
Required: Azure, Azure Databricks, Delta Lake, PySpark, Spark SQL, SQL, ETL/ELT development, data pipeline design, data modeling, data quality controls, production support, performance tuning, and stakeholder requirements clarification.
Strongly preferred: Azure Data Lake Storage, Azure Data Factory, Databricks Workflows, Git, CI/CD, DevOps practices, orchestration frameworks, metadata management, monitoring, and cost/performance optimization.
Nice to have: Structured Streaming, Auto Loader, Kafka, Event Hubs, CDC, incremental processing, near-real-time refresh patterns, and low-latency data pipelines.
The IT Senior Data Engineer will design, build, optimize, and support scalable data engineering solutions on a modern cloud-native data platform. The role will focus on developing reliable, secure, and high performing data pipelines, curated data layers, and analytics-ready data assets that support business operations, reporting, advanced analytics, and new strategic initiatives. This role requires a senior-level data engineer who can work independently across technical and business teams, clarify requirements directly with stakeholders, translate business needs into technical delivery plans, and ensure that data products are designed for quality, performance, reusability, and long-term maintainability.
We compare skills, grade, work format and salary
Most often 25,800 to 47,300
Grade
Senior
Experience
from 8 years
Work format
Hybrid
English level
B2, upper-intermediate
An email or a Telegram message to the recruiter
Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.
The IT Senior Data Engineer will design, build, optimize, and support scalable data engineering solutions on a modern cloud-native data platform. The role will focus on developing reliable, secure, and high performing data pipelines, curated data layers, and analytics-ready data assets that support business operations, reporting, advanced analytics, and new strategic initiatives. This role requires a senior-level data engineer who can work independently across technical and business teams, clarify requirements directly with stakeholders, translate business needs into technical delivery plans, and ensure that data products are designed for quality, performance, reusability, and long-term maintainability.
Minimum 8 years of professional data engineering experience, including hands-on design and delivery of enterprise-scale data pipelines, data platforms, ETL/ELT processes, and analytics-ready datasets.
Senior-level hands-on experience with Azure and Azure Databricks is required. Strong experience developing data engineering solutions using Databricks, PySpark, Spark SQL, Delta Lake, and SQL.
Strong understanding of cloud-native data engineering patterns, including scalable ingestion, transformation, orchestration, monitoring, performance tuning, and production support.
Experience building and maintaining data pipelines that process large volumes of structured, semi structured, and unstructured data from multiple source systems.
Strong experience with data modeling, data marts, curated data layers, and business-facing datasets for reporting, analytics, and operational consumption.
Strong ability to clarify requirements directly with stakeholders and translate business rules, data definitions, and process needs into technical implementation details.
Experience with source-to-target mapping, data profiling, data validation, reconciliation, and data quality management.
Experience with job orchestration and scheduling tools such as Azure Data Factory, Databricks Workflows, Airflow, or similar technologies.
Strong understanding of data governance, access control, metadata, lineage, security, and compliance considerations in a cloud data environment.
Experience with performance tuning and optimization of Spark jobs, Databricks clusters, SQL queries, and Delta tables.
Strong troubleshooting, problem-solving, and root-cause analysis skills in production data environments.
Strong communication skills, with the ability to explain technical concepts, risks, dependencies, and delivery options to business and technology stakeholders.
Ability to work independently with minimal supervision while collaborating effectively in cross-functional delivery teams.
Required: Azure, Azure Databricks, Delta Lake, PySpark, Spark SQL, SQL, ETL/ELT development, data pipeline design, data modeling, data quality controls, production support, performance tuning, and stakeholder requirements clarification.
Strongly preferred: Azure Data Lake Storage, Azure Data Factory, Databricks Workflows, Git, CI/CD, DevOps practices, orchestration frameworks, metadata management, monitoring, and cost/performance optimization.
Structured Streaming, Auto Loader, Kafka, Event Hubs, CDC, incremental processing, near-real-time refresh patterns, and low-latency data pipelines.
Connect and Celebrate: Participate in a variety of events including leisure, summer, family, social, and year-end gatherings
Set up: Hybrid
Schedule: Dayshift - 9AM - 6PM
Office location: Mandaluyong / BGC (client's office)
