Data Engineer

Job description

We are looking for a passionate and highly motivated Data Engineer to join our growing data team. In this role, you will work on building scalable data platforms, optimizing large-scale data pipelines, and enabling data-driven decision-making across the organization. You will collaborate closely with Data Scientists, Analysts, and business stakeholders to develop modern cloud-based data solutions using technologies such as Databricks, Snowflake, PySpark, SQL, and Python. If you enjoy solving complex data challenges and working in a fast-paced, innovative environment, we’d love to connect with you. Key Responsibilities: Design, build, and maintain scalable ETL/ELT pipelines for processing large volumes of structured and unstructured data Develop high-performance data processing solutions using PySpark and distributed computing frameworks Build, optimize, and manage data platforms on Databricks and/or Snowflake Write clean, efficient, and production-ready SQL queries and Python code for data transformation, automation, and analytics Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product teams, and Business stakeholders to deliver data-driven solutions Ensure data quality, governance, integrity, scalability, and reliability across enterprise data systems Monitor, troubleshoot, and optimize existing pipelines, workflows, and database performance Implement best practices around coding standards, testing, CI/CD, version control, and technical documentation Required Skills & Qualifications: 2–5 years of experience in Data Engineering or related roles Strong hands-on experience with Databricks and/or Snowflake Proficiency in SQL and Python programming Practical experience with PySpark and distributed data processing Solid understanding of Data Warehousing, ETL/ELT concepts, and Data Modeling Experience working with large-scale datasets in cloud-based environments Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field Preferred Skills: Experience with cloud platforms such as AWS, Azure, or GCP Familiarity with orchestration and transformation tools such as Airflow, dbt, or Azure Data Factory (ADF) Knowledge of Git, CI/CD pipelines, and DevOps best practices Exposure to Delta Lake, Lakehouse architecture, Kafka, Spark Streaming, or real-time data processing Experience working in Agile/Scrum environments is a plus Ascentt is transforming the future of manufacturing through advanced Data Analytics, AI/ML, and Generative AI solutions. We partner with global manufacturing enterprises to convert complex industrial data into actionable, real-time business insights. Our teams work on scalable, high-impact engineering challenges across cloud, data, and intelligent automation ecosystems. If you are passionate about innovation, solving complex problems, and building next-generation data platforms, Ascentt offers an exciting opportunity to create real-world impact at scale.