Data Engineer (English Speaker)

Job Title: Data Engineer (English Speaker)

Geography / Location: Jakarta, Indonesia (or remote)  

Company Information:  

Daniel P. O’Reilly and Company (DPO&Co.) is a boutique strategy consulting firm that specializes in rapidly delivering value to our clients. We engage with Private Equity firms and traditional corporate clients on projects similar to those done at A.T Kearney, McKinsey, Bain, BCG, Strategy&, etc. Additionally, our BPO (Business Process Outsourcing) services are specifically targeted to mid-market clients to improve any inefficiency in the back-office functions by leveraging labour cost arbitrage and time zone difference. BPO performs several services, including Finance & Accounting, CRM, Supply Chain, Data Analytics, HR, Admin functions, and many more based on our client’s specific needs. After several successful years and completing over 50 engagements, we have also entered the Principal Investing arena, closing our first deal on a Printed Circuit Board Manufacturing company in September 2020. The team spans globally with team members in Chicago, Puerto Rico, New Delhi, Colombia, Indonesia, and the Philippines. Our BPO team has tripled since 2020, and we are looking for new team members who could elevate our team’s experience and skills to the next level!  

Role Overview: 

We are seeking an Analytical/Data Engineer to build and maintain our enterprise data platform. You will be the primary bridge between our raw business data (CRM, ERP, and SaaS platforms) and our strategic analytics layer. Your mission is to develop scalable, high-performance analytical data pipelines that ensure data integrity, reliability, and accessibility across the organization. 

Key Responsibilities: 

• Universal Data Ingestion: Design and implement robust, reusable ingestion frameworks to pull data from diverse sources including REST APIs, relational databases, and flat files. You should be able to identify the most efficient extraction approach for new platforms while handling authentication (OAuth2), pagination, and rate limiting.  

• Lakehouse Architecture: Build and maintain our cloud-based Lakehouse environment using the Medallion Architecture (Bronze, Silver, and Gold layers). You will manage raw data ingestion and develop transformation logic that supports reliable analytical datasets.  

• Data Modeling & Warehouse Design: Develop and maintain analytical data models by transforming complex source data into clean, scalable structures optimized for reporting and business intelligence.  

• Advanced Orchestration: Build and monitor automated data pipelines. You will implement and maintain efficient data loading strategies, including incremental loading and, where applicable, Change Data Capture (CDC), to keep data fresh while minimizing load on source systems.  

• Code-Led Transformation: Utilize SQL and Python (PySpark/Pandas) to perform advanced data transformation and normalization. You will write modular, version-controlled code that is maintainable and reusable.  

• Governance & Compliance: Support data quality, security, and governance by implementing appropriate access controls, validation, and best practices to ensure reliable analytical datasets. 

Technical Requirements 

• Experience: 3–5 years of experience in Data Engineering or Analytics Engineering. Experience with Microsoft data platforms (Azure Synapse, Microsoft Fabric, Azure Data Lake Storage, and Power BI) is preferred. Candidates with experience in other cloud data platforms (AWS or GCP) who can quickly adapt to the Microsoft ecosystem are also encouraged to apply. 

• Cloud Ecosystems: Strong experience with the Microsoft data platform, particularly Microsoft Fabric, Azure Synapse Analytics, Azure Data Lake Storage, and Power BI. Experience with AWS or GCP is also valued, especially if you can quickly adapt your knowledge to Microsoft-based environments.  

• Engineering Excellence: Strong proficiency in Python and SQL. Comfortable developing custom data processing logic when standard connectors are not sufficient.  

• Big Data Standards: Experience building and maintaining data pipelines using Delta Lake and Parquet. Understanding of ACID transactions, schema evolution, partitioning, and cloud-based lakehouse architectures.  

• APIs & Integration: Proven experience integrating data from enterprise platforms such as Salesforce, SAP, Oracle, or similar ERP/CRM systems through APIs or other integration methods.  

• Analytics Engineering: Experience building Bronze, Silver, and Gold data models using SQL and PySpark. Ability to create reusable transformation logic and support Power BI semantic models for reporting.  

• Experience with automation tools (especially Power Automate) and data visualization platforms such as Power BI or Tableau is a plus.  

• Experience with version control (Git) and collaborative development practices for data engineering projects. 

Preferred Qualifications 

• Experience with Power BI semantic models.  

• Experience with Microsoft Fabric, Azure Synapse Analytics, and Azure Data Lake Storage. 

• Familiarity with Git-based development workflows and collaborative code reviews.  

• Experience supporting production data pipelines, including monitoring, troubleshooting, and backfills. 

Interested candidates should submit a resume and cover letter to HR at HR@dpoandco.com  

Please visit our website at https://dpoandco.com/bpo to learn more about us!