Data Engineer

Job Description

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.

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