Data Engineer
Summary
Designs and maintains scalable data pipelines and cloud-based data architectures to move, clean, and store data for analytics and reporting.
The Data Engineer will be responsible for designing, developing, and managing data pipelines and architectures. S/he will ensure that data flows seamlessly from multiple sources into databases, data lakes, or warehouses and is processed in a way that supports business analysis and decision-making. The ideal candidate will have strong software engineering skills, experience with data processing frameworks, and the ability to optimize and scale large data systems.
The Benefits
At Stratpoint, we enjoy the autonomy, lack of bureaucracy, and the freedom to experiment but without the chaos. We’re like a startup but with adult supervision.
You will be supported by capable management of HR, Finance and IT that adheres to the highest standards of integrity and good governance. Hybrid is our mode of work, but when we need to come together, we have inviting open floor office spaces designed to spark gatherings, collaboration, and camaraderie.
Your Responsibilities
- Design, build, and maintain scalable data pipelines that support data collection, transformation, and integration from various sources.
- Maintain databases, data warehouses, data lake ensuring data integrity, scalability, and reliability.
- Implement efficient ETL/ELT (Extract, Transform, Load) processes to automate data collection, cleaning, and transformation tasks.
- Integrate data from various internal and external sources, including APIs, cloud storage, third-party systems, and databases.
- Optimize data architectures for performance, scalability, and cost efficiency. Ensure fast and reliable data retrieval.
- Work closely with the data team to understand data needs and deliver reliable, clean, and accessible data solutions.
- Implement data validation and monitoring processes to ensure data accuracy and integrity. Identify and troubleshoot data issues and bottlenecks.
- Manage and optimize cloud-based infrastructure (e.g., AWS, Azure) to support data storage, processing, and retrieval.
- Automate repetitive tasks and processes using scripting languages (e.g., Python and SQL) and workflows.
- Document data architectures, pipelines, and workflows that will be understood by the Information Technology (IT) department. Provide technical support and troubleshooting to the team.
- Demonstrating a strong track record of interacting with the business and technology partners to drive the requirement, technical process into acceptance criteria.
- Keen on performing user live verification and testing to avoid errors before going to the production environment.
- Provide support for data extraction and reports as required.
About You
- Degree in Computer Engineering / Data Science / Statistics / Physics or any other related field in IT
- Knowledge in Agile methodology (e.g. Scrum & Kanban)
- Experienced in using cloud computing platforms (Azure)
- Coding Languages (Python / PySpark, SQL, DAX)
- File types (Parquet, SQL, CSV, XLSX, JSON, TXT)
- Systems / Softwares / Platforms (Github, Databricks, AWS, PowerBI, Linux)
- Other Qualifications (ETL/ELT, Integration, API, Statistics, Code/Performance Optimization, Data Wrangling)
The requirements listed in this job description are guidelines, not hard and fast rules. You don’t have to satisfy every requirement or meet every qualification listed. If your skills are transferable and you are in the ballpark of what we are looking for, we encourage you to submit an application. We look forward to getting to know you more!