Data Engineer (CIT05192026)

Buddle

20d

About The Position

We are looking for a Data Engineer who is passionate about building scalable data pipelines, analytics systems, and reporting workflows that help drive smarter business decisions and improve customer experiences. In this role, you’ll play an important part in transforming raw data into meaningful insights through reliable, efficient, and well-structured data solutions. You’ll work closely with cross-functional teams across Engineering, Product, Operations, Legal, and Analytics to develop scalable data and backend solutions that support the company’s growth and strategic goals. We’re looking for someone who enjoys solving problems, thrives in collaborative and fast-paced environments, and is excited to continuously learn and adapt to new technologies and evolving business needs.

Requirements

1–3 years of experience in data engineering, analytics, or software engineering
Strong understanding of data pipelines, databases, and reporting systems
Hands-on experience with SQL, Python, and data transformation workflows
Familiarity with cloud platforms such as AWS, GCP, or Azure
Exposure to modern data platforms including Databricks, Snowflake, Airflow, or DBT
Experience working with dashboards and reporting tools such as Power BI or similar BI platforms
Strong problem-solving and analytical thinking skills
Ability to quickly learn new technologies and adapt to evolving environments
Comfortable working in agile, fast-paced, and collaborative teams

Nice To Haves

Exposure to fintech, payments, financial systems, or large-scale datasets is an advantage but not required

Responsibilities

Design, build, and maintain ETL/ELT pipelines for structured and unstructured datasets
Process and analyze customer, operational, and financial transaction data
Develop scalable data workflows and reusable scripts for automation and reporting
Maintain data models, metric definitions, and analytics documentation
Optimize SQL queries and improve data processing performance and reliability
Integrate external data sources such as ABS and Census datasets into existing databases
Support cloud-based data platforms and modern data lakehouse environments
Build dashboards and reports for internal and external stakeholders
Translate business requirements into actionable analytics and reporting solutions
Support KPI tracking, operational reporting, and customer behavior analysis
Help identify trends, anomalies, and opportunities through data-driven insights
Provide insights that support operational, legal, and growth-related decision-making
Collaborate with engineers, analysts, and stakeholders in agile environments
Participate in planning, testing, debugging, and deployment activities
Contribute ideas to improve workflows, system reliability, and engineering processes
Adapt quickly to changing priorities and evolving business requirements
Support development of reusable templates, modular scripts, and data engineering best practices
Support additional engineering or analytics initiatives as needed
Identify opportunities to improve processes, systems, and performance
Contribute to a collaborative and high-performing team environment
Assist in maintaining data quality, governance, and documentation standards