Data Engineer

About ARAs Client

ARAs Client is a fast-growing technology-driven organization focused on building scalable, cloud-native data platforms and intelligent analytics ecosystems. The company partners with enterprise stakeholders to transform large-scale data into actionable business insights through modern engineering practices and distributed data technologies.

Role Summary

ARAs Client Delta is seeking a skilled and motivated Data Engineer with strong expertise in Databricks, Python, PySpark, Apache Airflow, SQL, and cloud-based data platforms. The ideal candidate will have hands-on experience designing scalable ETL/ELT pipelines, orchestrating workflows, and building reliable data infrastructure to support analytics and business operations.

This role requires someone who thrives in a collaborative, fast-paced environment and is passionate about building clean, scalable, and maintainable data solutions.

Key Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for enterprise data workloads.
• Develop distributed data processing solutions using Databricks and PySpark.
• Build and manage Apache Airflow DAGs for workflow orchestration and automation.
• Collaborate with analytics, product, and engineering teams to understand and translate business requirements into technical solutions.
• Develop optimized SQL queries and support data modelling initiatives.
• Manage ingestion, storage, and partitioning strategies using Amazon S3 within modern data lake architectures.
• Ensure high levels of data quality, reliability, observability, and performance.
• Contribute to platform optimization, documentation, governance, and engineering best practices.
• Participate in debugging, troubleshooting, and performance tuning activities.
• Support CI/CD and scalable deployment practices within cloud-native environments.

Must-Have Qualifications

• 25 years of hands-on experience in Data Engineering, ETL Development, or Analytics Engineering.
• Strong proficiency in Python programming.
• Hands-on expertise with Databricks and PySpark.
• Experience building and maintaining Apache Airflow DAGs.
• Advanced SQL skills including optimization and performance tuning.