Data Engineer

Ascent, LLC
Plano, United States
26 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Airflow Amazon Web Services Data Analysis Microsoft Azure Big Data Cloud Computing Information Systems Continuous Integration Data Architecture Information Engineering Extract Transform Load (ETL) Data Transformation
+25 more
Data Systems Data Warehousing DevOps Distributed Computing Environment Python (Programming Language) SQL Databases Unstructured Data Data Processing Google Cloud Azure Data Factory Snowflake Database Performance Git Data Lakes Pyspark Information Technology Data Analytics Apache Kafka Spark Streaming Data Management Software Coding Stream Processing Software Version Control Data Pipelines Databricks

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., * 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

Requirements

  • 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 Google Cloud Platform
  • 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

About the company

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.

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