Engineer - Data Engineering

WE ARE HIRING: Engineer – Data Engineering

Location: Sri Lanka
Employment Type: Contract
Company Industry: Software
Role Overview

We are seeking a motivated and technically skilled Engineer – Data Engineering to design, develop, and maintain scalable enterprise data solutions and cloud-based data-processing applications.

The selected candidate will be responsible for building reliable data pipelines, integrating multiple source systems, processing large volumes of data, and supporting solutions throughout the complete software-development lifecycle. The role requires strong programming skills, hands-on cloud experience, and the ability to work effectively within an Agile and DevOps environment.
Key Responsibilities

- Design and develop scalable enterprise-grade data-processing solutions.

- Build distributed and highly available data applications that support large-scale business requirements.

- Design, develop, test, and maintain data pipelines connecting multiple source systems and target platforms.

- Develop ETL and ELT workflows for batch and near-real-time data processing.

- Process, transform, and validate large volumes of structured and unstructured data.

- Develop cloud-native data solutions using Google Cloud Platform services.

- Build data-processing and orchestration workflows using tools such as Airflow and Cloud Composer.

- Work with services such as BigQuery, Dataflow, Dataproc, Datastream, Pub/Sub, Cloud Functions, and Cloud Run.

- Support data-processing solutions using AWS services such as Glue, Lambda, EMR, and Data Pipeline when required.

- Develop data-processing applications using Python, Shell scripting, and SQL.

- Design and optimize solutions using relational databases, NoSQL databases, and distributed storage engines.

- Support streaming-data applications using technologies such as Kafka, Pub/Sub, Spark, or similar tools.

- Contribute to the development of data warehouses, data marts, data lakes, and data-mesh solutions.

- Apply software-engineering best practices to ensure clean, reusable, maintainable, and high-quality code.

- Participate in code reviews, technical design discussions, and solution-architecture activities.

- Implement and maintain Continuous Integration and Continuous Delivery pipelines.

- Use code-management and automation tools such as GitHub, GitLab, Jenkins, or equivalent platforms.

- Follow DevOps principles throughout development, testing, deployment, and production support.

- Monitor application health, data-pipeline performance, and system reliability.

- Investigate and resolve data-processing failures, performance issues, and production incidents.

- Use monitoring platforms such as Datadog or equivalent tools when required.

- Collaborate with software engineers, data engineers, quality engineers, analysts, architects, and product stakeholders.

- Participate in Agile activities, including sprint planning, daily stand-ups, reviews, and retrospectives.

- Support technical alignment across team members and contribute to implementation planning.

- Maintain technical documentation, data mappings, solution designs, and operational procedures.

- Continuously evaluate new data-engineering tools, cloud services, and development practices.

Candidate Profile

- Bachelor's degree in Computer Science, Software Engineering, Information Technology , or an equivalent field.

- Minimum 1 to 2 years of experience developing enterprise-grade data-processing applications.

- Strong programming skills in Python, Shell scripting, and SQL .

- Hands-on experience processing large volumes of data.

- Experience designing and developing ETL or ELT data pipelines.

- Practical experience with relational databases, NoSQL databases, and distributed storage engines.

- Hands-on experience with Google Cloud Platform .

- Experience with GCP services such as BigQuery, Dataflow, Dataproc, Datastream, Pub/Sub, Cloud Functions, Cloud Run, and Cloud Composer .

- Familiarity