Data Engineer (DATABRICKS / PYSPARK) at Sigma Software
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About this role
Develop and maintain data pipelines for processing large volumes of data in batch and near real-time environments
Work with Databricks, PySpark, and SQL to transform, validate, and optimize data
Support implementation of Data Lakehouse solutions following engineering standards and best practices
Build, test, and automate ETL processes and data workflows
Improve data quality, organization, and reliability across platforms
Collaborate with engineers, analysts, and stakeholders to deliver scalable solutions
Troubleshoot, optimize, and monitor data pipelines
Stay up to date with modern data engineering technologies
Ensure deliverables meet quality standards and project requirements
2+ years of experience in Big Data development and database design
Strong hands-on experience with SQL
Strong Python development skills
Hands-on experience with PySpark
Experience developing and maintaining data pipelines in Databricks
Experience with Delta Lake
Experience with Medallion Architecture (Bronze, Silver, Gold layers)
Strong analytical and problem-solving skills
Intermediate or higher English level
WILL BE A PLUS Experience with AWS services, including S3 We are looking for a Middle Data Engineer to join our team and contribute to building scalable data solutions for a leading AdTech and analytics company. In this role, you will work with modern Data Lakehouse architecture, high-load distributed systems, and cloud-native technologies while helping process large volumes of marketing and advertising data in batch and near real-time environments. This is an excellent opportunity for engineers who want to deepen their expertise in Databricks, PySpark, Delta Lake, and scalable data platforms while collaborating with experienced data engineering professionals on enterprise-scale solutions. About Sigma Software : Sigma Software is a global IT consulting company delivering software development and IT consulting services to clients worldwide across multiple industries. CUSTOMER Our customer is a leading AdTech and data analytics company specializing in high-load platforms for large-scale data processing and analytics. The company develops cloud-based solutions that help businesses manage data, build analytical models, and generate actionable insights for marketing and advertising operations. The customer operates globally and focuses on scalable microservices architecture, modern engineering practices, and enterprise-grade analytics platforms. PROJECT The project focuses on developing and supporting scalable Data Lakehouse solutions for processing large volumes of marketing and advertising data. The team works with batch and near real-time data pipelines, cloud-native infrastructure, and modern big data technologies. Key Technologies: Databricks, PySpark, Python, SQL, Delta Lake, Medallion Architecture, ETL Pipelines, AWS S3 Originally posted on Himalayas