Design and deliver AI-ready data platforms, pipelines, and semantic layers for client engagements, translating business needs into scalable analytics solutions and supporting AI-enabled workflows from design through production.
Senior Data Engineer
📜 Description
- Build and maintain pipelines to ingest, transform, and normalize data from multiple sources.
- Design scalable, reliable data ingestion architectures in Snowflake.
- Implement validation rules, checks, and monitoring to maintain data quality.
- Process large datasets with SQL and Python for analytics and reporting.
- Support ETL and file-ingestion workflows for structured and semi-structured data.
- Collaborate with stakeholders and document and improve data processes and standards.
🛠️ Requirements
- 4+ years of experience in Data Engineering or Data Analytics roles with strong engineering focus.
- Strong hands-on experience with Snowflake (Must).
- Strong hands-on experience with Python for data processing and transformation.
- Strong experience with SQL and working with large-scale datasets.
- Proven experience in data validation, data transformation, and normalization.
- Experience building and maintaining ETL pipelines and handling data ingestion workflows.
- Strong attention to detail with a focus on data quality and reliability.
- Ability to work in cross-functional environments and communicate effectively with stakeholders.
- Experience working with Salesforce data structures.
- Familiarity with Tamarac or similar RIA platforms.
✨ Benefits
- AWS, Databricks, and Snowflake certifications.
- AI learning paths, study plans, courses, and role-tailored certifications.
- Udemy Business access.
- English lessons.
- Travel opportunities to industry conferences and meet clients.
- Career development plans and mentorship programs.
- Rewards for birthdays, work anniversaries, and personal milestones.
- Company-provided equipment and flexible working options.
Full job description
Company Description
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. 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
Job Description
We’re looking for a Senior Data Engineer to support the design, development, and optimization of data solutions for a high-impact enterprise initiative. This role is ideal for someone with strong hands-on experience in data processing, transformation, and validation, who thrives in building reliable and well-structured datasets for analytics and business workflows.
You will work closely with cross-functional teams to ensure data is accurate, standardized, and ready for downstream consumption, contributing to scalable and high-quality data pipelines.
What will you be doing?
- Design, develop, and maintain data pipelines to ingest, transform, and normalize data from multiple sources.
- Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability.
- Apply best practices in data validation to ensure accuracy, consistency, and reliability across datasets.
- Perform data transformation and normalization to support analytics and reporting use cases.
- Work with large datasets using SQL and Python to process and analyze data efficiently.
- Ensure data quality by implementing validation rules, checks, and monitoring processes.
- Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable solutions.
- Support ETL processes and file handling workflows for structured and semi-structured data.
- Contribute to documentation and continuous improvement of data processes and standards.
Qualifications
What are we looking for?
- 4+ years of experience in Data Engineering or Data Analytics roles with strong engineering focus.
- Strong hands-on experience with Snowflake (Must).
- Strong hands-on experience with Python for data processing and transformation.
- Strong experience with SQL and working with large-scale datasets.
- Proven experience in data validation, data transformation, and normalization.
- Experience building and maintaining ETL pipelines and handling data ingestion workflows.
- Strong attention to detail with a focus on data quality and reliability.
- Ability to work in cross-functional environments and communicate effectively with stakeholders.
Nice to have:
- Experience working with Salesforce data structures.
- Familiarity with Tamarac or similar RIA platforms.
- Experience with Compass or SharePoint integrations.
- Experience with file handling and ingestion processes (e.g., CSV, JSON, batch files).
Additional Information
Our Perks and 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.
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