Data Engineer (Finance data Integration) - Hybrid Work Type

Directio Sp. z o.o. Open · verified Oct 24, 2026

Fort Bonifacio Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Directio Sp. z o.o. Fort Bonifacio.

Pay not stated Data Engineer salary

RoleData Engineering

SeniorityMid-level

LocationFort Bonifacio

PostedJun 10, 2026 · 4mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build and maintain Azure pipelines that bring in data, transform it, and prepare it for analytics
Clean and combine data from multiple sources, checking that it stays reliable and consistent for reporting
Shape finance, accounting, ERP, and other business data for reporting, predictive analysis, and decision-making
Work with data science, analytics, and business teams to deliver scalable data solutions
Use Oracle, SQL, PySpark, REST APIs, and Azure services within an Agile delivery process

What you bring

At least five years in data warehousing, ETL/ELT, or data engineering, building enterprise data solutions
Expert-level knowledge of Azure Data Factory, Databricks, ADLS Gen2, Delta Lake, and Azure SQL Database
Hands-on experience developing Azure data pipelines and working with Oracle Database, PL/SQL, and Oracle ODI
Strong SQL and dimensional modeling skills, plus experience with PySpark and ERP or finance data
Experience with cloud object storage and REST API integrations

Who this fits

This mid-level role suits a data engineer who has worked with finance or accounting data and enterprise Azure pipelines. You must work onsite in Makati three days each week, with two work-from-home days. The project runs for six months, with a possibility of extension.

From the employer

Directio is a global IT services company. We consult, code, test, deploy, and manage mainly cloud-based and mobile applications, providing around-the-clock support from our offices in Poland, the Philippines, Mexico, and the USA. We prepare our FMCG, retail, automotive, and SaaS clients for the future by accelerating their digital transformation. Operating under the “We Code Success” principle, we prioritize the success of our clients, consultants, and partners.

About project: 

We are looking for a Data Engineer for our international client who operates in the maritime transportation and logistics sector. The organization manages complex global shipping operations, delivering vehicles, machinery, and industrial cargo worldwide. By leveraging advanced technologies and data-driven decision-making, the company is committed to improving operational efficiency, enhancing customer experience, and supporting sustainable business growth.

This is a 6-month project with the possibility of extension

Responsibilities

As a Data Engineer, you will work closely with Data Science, Analytics, and business teams to design, build, and optimize scalable data solutions supporting reporting, advanced analytics, and data-driven decision-making.
You will design and maintain data ingestion and transformation pipelines using the Microsoft Azure data stack, especially Azure Data Factory, Azure Databricks, ADLS Gen2, Delta Lake, and Azure SQL Database.
You will extract, cleanse, transform, and aggregate data from multiple sources, ensuring data quality, consistency, reliability, and availability for analytical workloads.
You will model frontend, backend, ERP, finance, and accounting data sources to support business intelligence, reporting, predictive analytics, and strategic decision-making.
You will work with Oracle Database, PL/SQL, Oracle ODI, SQL, RDBMS technologies, PySpark, REST APIs, and Azure-based data platforms in an Agile delivery environment.

Requirements

5+ years of experience in Data Warehousing, ETL/ELT, or Data Engineering, with proven experience designing and maintaining enterprise data solutions.

SME-level experience with the Microsoft Azure data stack, especially:Azure Data Factory,Azure Databricks, ADLS Gen2,Delta Lake / Delta format, Azure SQL Database
Strong hands-on experience with Azure-based data pipelines, including data ingestion, transformation, storage, modeling, and analytical consumption.
Experience with Oracle Database and PL/SQL for database development and data processing.
Mid-level or higher experience with Oracle ODI for data integration and ETL/ELT processes.
Experience with PySpark, preferably in Azure Databricks environments.
Strong SQL skills and experience with RDBMS technologies and dimensional data modeling.
Experience with ERP-related projects and finance or accounting datasets.
Experience with S3, Object Storage, or cloud data lake storage solutions.
Experience with REST API integrations.
Ability to work in a hybrid setup: 3 days onsite in Makati and 2 days work from home. This is a necessary condition.