Data Engineer

5 days ago

noida, India TechioSoft Full time

TechioSoft is a dynamic and forward-thinking software solutions company that partners with leading enterprises to deliver cutting-edge data-driven technologies. Our team is dedicated to creating robust solutions that address complex business challenges, with a strong focus on scalability, security, and innovation.

We are currently seeking a skilled Data Engineer to join our team and help drive our data initiatives. You will play a key role in building and optimizing our data pipelines, ensuring seamless integration with our products and platforms.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and process large datasets from various sources.
  • Collaborate with cross-functional teams (data scientists, software engineers, product managers) to understand data requirements and implement robust solutions.
  • Ensure data quality and integrity throughout the data lifecycle, implementing best practices for data governance.
  • Optimize data storage solutions for performance, scalability, and cost-efficiency.
  • Work with both structured and unstructured data to support real-time data processing and analytics.
  • Automate data workflows and implement monitoring solutions to ensure data pipeline reliability and availability.
  • Continuously evaluate and integrate new tools and technologies that align with the company’s data strategy.
  • Participate in code reviews and contribute to engineering best practices.

Qualifications:

  • 3+ years of experience as a Data Engineer or in a similar role.
  • Proven experience with SQL, Python, and ETL/ELT tools.
  • Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for data storage and processing.
  • Familiarity with Big Data technologies such as Apache Spark, Hadoop, or similar frameworks.
  • Experience working with data lakes and data warehouses (e.g., Redshift, Snowflake).
  • Strong understanding of data modeling and data architecture best practices.
  • Proficiency with version control systems, such as Git, and continuous integration/deployment tools.
  • Experience in optimizing data pipelines and workflows for performance and scalability.
  • Excellent problem-solving skills, attention to detail, and the ability to work independently as well as part of a team.

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