Data Engineer Analyst

What is this position about? Design, build, and maintain scalable data pipelines and ingestion frameworks supporting batch processing, streaming, and change data capture (CDC) patterns.

About Blend360

• With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence.
• The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy.
• We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients.
• For more information, visit www.blend360.com We are seeking a Data Engineer Analyst to contribute to our next level of growth and expansion.

Responsibilities

• 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.

Requirements

• 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.
• Familiarity with AI-assisted development workflows and engineering productivity tools What about languages?
• Advanced (required for effective communication with global teams) How much experience must I have?
• 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.

Preferred

• Experience with infrastructure-as-code or pipeline orchestration tools (e.g., Airflow, Step Functions, dbt) is a plus.

Benefits

• 📚 Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
• Access to AI learning paths to stay up to date with the latest technologies.
• Study plans, courses, and additional certifications tailored to your role.
• Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
• English lessons to support your professional communication. 👨🏽‍💻 Travel opportunities to attend industry conferences and meet clients. 👩‍🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
• Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance.
• Other benefits may vary according to your location in LATAM.
• For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
• Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people.