Data Engineer

1 week ago

Gurgaon, Haryana, India Oneture Technologies Full time ₹ 15,00,000 - ₹ 25,00,000 per year

About Oneture Technologies
Founded in 2016, Oneture is a cloud-first, full-service digital solutions company, helping clients harness the power of Digital Technologies and Data to drive transformations and turning ideas into business realities. Our team is full of curious, full-stack, innovative thought leaders who are dedicated to providing outstanding customer experiences and building authentic relationships. We are compelled by our core values to drive transformational results from Ideas to Reality for clients across all company sizes, geographies, and industries.

Oneture team delivers full lifecycle solutions—from ideation, project inception, planning through deployment to ongoing support and maintenance. Our core competencies and technical expertise includes Cloud powered: Product Engineering, Big Data and AI ML. Our deep commitment to value creation for our clients and partners and "Startups-like agility with Enterprises-like maturity" philosophy has helped us establish long-term relationships with our clients and enabled us to build and manage mission-critical platforms for them.

About The Role
We are seeking a Data Engineer to design and maintain scalable data pipelines that power finance-related analytics and reporting. This role involves partnering closely with finance, product, and business teams to translate requirements into robust technical solutions while ensuring data accuracy, consistency, and performance.

You will work with modern data technologies—including SQL,Python, Spark, Airflow, and AWS cloud services—to build efficient workflows, optimize large-scale datasets, and deliver business-critical insights.

Role & Responsibilities

  • Design, build, and maintain scalable data pipelines for finance-related datasets.
  • Partner with finance stakeholders (product & business teams) to understand requirements and translate them into robust technical solutions.
  • Ensure data accuracy, consistency, and timeliness across reporting layers and downstream systems.
  • Optimize SQL queries and Spark jobs for large-scale datasets to improve performance and cost efficiency.
  • Implement scheduling, orchestration, and monitoring of workflows using Airflow (or similar tools).
  • Collaborate with cross-functional teams (Finance, Product, Analytics, Engineering) to deliver business-critical solutions.
  • Adhere to best practices for coding, testing, and deployment in AWS cloud environments.

Key Skills & Requirements

  • 1.5–3 years of experience as a Data Engineer or in a related role.
  • Strong proficiency in Python and SQL.
  • Hands-on experience with Apache Spark (PySpark preferred).
  • Experience with Airflow (or other orchestration tools).
  • Working knowledge of AWS services (S3, EMR, Glue, Redshift, etc.).
  • Strong problem-solving skills with the ability to convert business needs into technical solutions.
  • Effective communication skills to collaborate with both technical and non-technical stakeholders.

Good to Have

  • Experience with Delta Lake / Data Lake architectures.
  • Knowledge of CI/CD, DevOps practices, and observability tools.
  • Exposure to SAP RISE environments.

Skills:- Python, PySpark, SQL, Amazon Web Services (AWS), Apache Airflow and Amazon Redshift

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