[Hiring] Data Engineer Analyst @Blend360

Role Description

We are seeking a Data Engineer Analyst to contribute to our next level of growth and expansion.

• Design, build, and maintain scalable data pipelines and ingestion frameworks supporting batch processing, streaming, and change data capture (CDC) patterns.
• Develop and optimize data processing workflows using Apache Spark and PySpark, ensuring reliable and performant transformation across large datasets.
• Implement and manage data lake architectures on AWS, leveraging S3 as the primary storage layer and Apache Iceberg for table format management, schema evolution, and time-travel capabilities.
• Work with AWS-native services including Glue for ETL orchestration, Athena for serverless querying, and Lambda for event-driven data processing.
• Manage data access controls and security configurations using AWS IAM, ensuring compliant and least-privilege access across the data platform.
• Collaborate with data analysts, data scientists, and platform engineers to understand data requirements and deliver production-ready solutions.
• Monitor pipeline health, troubleshoot data quality issues, and implement improvements to ensure data reliability and freshness.
• Contribute to the documentation of data flows, architecture decisions, and engineering standards within the team.

Qualifications

• Advanced hands-on experience with AWS services, including:
  • AWS Glue
  • Amazon S3
  • Amazon Athena
  • AWS IAM
• Apache Spark / PySpark for data processing.
• Data lake architectures, ideally with knowledge of Apache Iceberg.
• Data ingestion patterns, including batch processing, streaming, and CDC patterns.
• Experience with SQL for data querying, validation, and exploratory analysis.
• Solid understanding of data modeling and large-scale data processing.
• Ability to work collaboratively in cross-functional teams and communicate technical concepts clearly to non-technical stakeholders.
• Experience with infrastructure-as-code or pipeline orchestration tools (e.g., Airflow, Step Functions, dbt) is a plus.
• Familiarity with AI-assisted development workflows and engineering productivity tools.

Requirements

• English: Advanced (required for effective communication with global teams).
• 2+ years of experience in Data Engineering or related roles, with hands-on work building and maintaining cloud-based data pipelines and lake architectures on AWS.

Benefits

• 💰 Compensation & Financial Benefits:
  • Christmas Bonus.
  • Saving Fund.
  • Food/grocery vouchers.
  • Home Office allowance.
• 🏥 Health & Insurance:
  • MetLife Life Insurance with funeral coverage.
  • MetLife Medical Insurance including dental discounts and vision plan.
  • Dependents optional with additional cost.
• 🗓️ Time Off & Holidays:
  • Vacation days with annual increases based on tenure.
  • Vacation premium.
  • Official holidays by law.
  • Holy week.
  • Day of the Dead.
  • Christmas Eve.
• ⚖️ Work-Life Balance:
  • Flexible working options to help you strike the right balance.
• 📚 Learning Opportunities:
  • Study plans, courses, and professional development opportunities.
  • English lessons to support your professional communication.