Data Engineer

Software Finder; Punjab; On-site; PKR 1,800,000 - 3,000,000; Full time

Job summary

Software Finder is seeking a Data Engineer to design and maintain end-to-end data pipelines on AWS, driving reliable datasets for BI and analytics. You will work with SQL, Python, and ETL/ELT processes across multiple source systems, with emphasis on data quality and observability.

The role emphasizes working with BI teams to improve data accuracy, build scalable data models, and ensure smooth data-driven decision making for business insights.

Qualifications

• Bachelor’s degree in CS/Engineering/IT or related field.
• 2–3 years of data engineering or data-focused backend experience.
• Strong SQL skills with complex query optimization.
• Proficient Python for data pipeline development and processing.
• Hands-on AWS data services experience (S3, Glue, Redshift, Lambda, Athena, EventBridge).
• Experience with Apache Airflow or AWS Step Functions.
• Solid data modeling fundamentals (Normalization, Dimensional Modeling).
• Familiarity with Git and collaborative workflows.
• Ability to troubleshoot data-quality issues and bottlenecks.
• Strong analytical, problem-solving and cross-functional communication skills.
• Experience with dbt is a plus; Terraform and CI/CD tooling preferred.
• Awareness of data governance, validation and quality-control practices.

Responsibilities

• Design, build, deploy, and maintain scalable ETL/ELT pipelines using AWS.
• Ingest, process, and transform data from multiple sources into the data warehouse.
• Write and optimize complex SQL queries for transformation and analytics.
• Develop data models to support BI dashboards and reporting.
• Orchestrate data workflows with Airflow or similar tools.
• Monitor pipeline performance, data freshness, and failures; implement fixes.
• Collaborate with BI teams to improve data accuracy and reliability.
• Document pipelines, models, and system dependencies; participate in code reviews.
• Contribute to backend and software engineering initiatives as needed.

Skills

SQL

Python

Data modeling

ETL/ELT

Airflow

Git

Analytical thinking

Cross-functional

Troubleshooting

AI coding assistants

Education

Bachelor’s degree in Computer Science / Engineering / Data Science

Tools

AWS S3

AWS Glue

AWS Redshift

AWS Lambda

AWS Athena

AWS EventBridge

Apache Airflow

dbt

Terraform

GitHub Actions

CodePipeline

Observability

Job description

Data Engineer

Software Finder is seeking skilled and motivated Data Engineers to join its growing Data Engineering team. This AWS-focused role involves building and managing data pipelines end to end, from ingestion and transformation to delivering reliable datasets that support business intelligence, analytics, and strategic decision-making.

The ideal candidate will have strong SQL and Python skills, practical experience with AWS data services, and a solid understanding of data modeling and workflow orchestration. The data products developed in this role will support revenue-generating systems and business analytics, with opportunities to contribute to broader software engineering initiatives.

Key Responsibilities

• Design, build, deploy, and maintain scalable ETL/ELT pipelines using AWS services.

• Ingest, process, and transform data from multiple source systems into the organization’s data warehouse.

• Write, optimize, and maintain complex SQL queries for data transformation, modeling, reporting, and analytics.

• Develop reliable data models that support business intelligence dashboards, reporting, and business analysis.

• Orchestrate data workflows using Apache Airflow, AWS Step Functions, or similar technologies.

• Monitor pipeline performance and data freshness, investigate failures, and implement sustainable solutions.

• Collaborate with Business Intelligence teams to improve data accuracy, consistency, and reliability.

• Establish effective feedback loops between Data Engineering and Business Intelligence teams to address data-quality issues.

• Identify and resolve pipeline bottlenecks, data discrepancies, and recurring operational problems.

• Improve pipeline scalability, performance, observability, and cost efficiency.

• Apply data validation and quality-control practices throughout pipeline development and maintenance.

• Use AI-assisted development tools, such as Claude Code, to support development and iteration.

• Participate in code reviews and follow established software engineering and version-control standards.

• Maintain clear technical documentation for data pipelines, models, workflows, and system dependencies.

• Support broader backend and software engineering initiatives as business and team needs evolve.

• Contribute to additional data engineering and technology-related projects as required.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline.

• 2–3 years of professional experience in data engineering or a backend or software engineering role involving substantial data-related work.

• Strong SQL skills, including experience writing and optimizing complex queries.

• Proficiency in Python for data pipeline development, automation, and data processing.

• Hands-on experience with AWS data services such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon Athena, and Amazon EventBridge.

• Practical experience with Apache Airflow or AWS Step Functions for workflow orchestration.

• Strong understanding of data modeling fundamentals, including normalization and dimensional modeling.

• Familiarity with Git and collaborative software development workflows.

• Ability to troubleshoot data-quality issues, pipeline failures, and performance bottlenecks.

• Strong analytical, problem-solving, and cross-functional communication skills.

• Experience with dbt for SQL-based data transformation is preferred.

• Familiarity with Terraform or other infrastructure-as-code tools is preferred.

• Experience with CI/CD pipelines using GitHub Actions, AWS CodePipeline, or similar tools is preferred.

• Experience with data monitoring, observability, and pipeline cost optimization is preferred.

• Familiarity with AI coding assistants such as Claude Code is preferred.

• Understanding of data governance, validation, and quality-control practices is preferred.

• Interest in expanding into backend or broader software engineering responsibilities is preferred.