Senior Data Engineer
Guadalajara, Jal., Mexico
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingRun daily data quality checks, SQL validations, and row-count monitoring
Investigate data anomalies such as nulls, duplicates, and missing intervals
Coordinate versioned data product releases, tests, release notes, and go/no-go decisions
From the employer’s posting
Develop and manage daily data quality checks, including SQL validations, threshold-based alerts, and row-count monitoring.
Investigate data anomalies such as nulls, duplicates, missing intervals, and unexpected data distributions, resolving issues before they affect downstream systems.
Coordinate versioned data product releases, including test case development, release notes, go/no-go decisions with end users, and patches through a structured release process.
What you’ll bring
All qualificationsCore experience
- Strong proficiency in SQL, including window functions (LAG, PARTITION BY), grouping sets, null handling, and Athena-specific query patterns.
- Experience working with telecommunications or network operations data, including modem telemetry, outage records, or IPDR-style data feeds.
- Experience with Python for scripting, automation, and data validation.
- Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions.
- Experience using Spark for large-scale data processing, preferably on EMR.
- Strong understanding of data quality and the ability to investigate anomalies, identify root causes, and determine when data does not look correct.
Qualification wording
Strong proficiency in SQL, including window functions (LAG, PARTITION BY), grouping sets, null handling, and Athena-specific query patterns.
Experience working with telecommunications or network operations data, including modem telemetry, outage records, or IPDR-style data feeds.
Experience with Python for scripting, automation, and data validation.
Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions.
Experience using Spark for large-scale data processing, preferably on EMR.
Strong understanding of data quality and the ability to investigate anomalies, identify root causes, and determine when data does not look correct.
Tools in this posting
- Python
- SQL
- AWS
- Databricks
- S3
- Spark
- Snowflake
Source — Tool mentions in context
- Strong proficiency in SQL, including window functions (LAG, PARTITION BY), grouping sets, null handling, and Athena-specific query patterns. - Experience with Python for scripting, automation, and data validation. - Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions.
- Build and maintain scalable ETL pipelines using AWS Glue, Spark, and Athena to process modem telemetry, outage events, and customer impact data. - Develop and manage daily data quality checks, including SQL validations, threshold-based alerts, and row-count monitoring. - Investigate data anomalies such as nulls, duplicates, missing intervals, and unexpected data distributions, resolving issues before they affect downstream systems.
Qualifications - Strong proficiency in SQL, including window functions (LAG, PARTITION BY), grouping sets, null handling, and Athena-specific query patterns. - Experience with Python for scripting, automation, and data validation.
Responsibilities - Build and maintain scalable ETL pipelines using AWS Glue, Spark, and Athena to process modem telemetry, outage events, and customer impact data. - Develop and manage daily data quality checks, including SQL validations, threshold-based alerts, and row-count monitoring.
- Experience with Python for scripting, automation, and data validation. - Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions. - Experience using Spark for large-scale data processing, preferably on EMR.
📚 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.
- Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions. - Experience using Spark for large-scale data processing, preferably on EMR. - Strong understanding of data quality and the ability to investigate anomalies, identify root causes, and determine when data does not look correct.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 13, 2026 · 16 days ago
- Recorded sightings
- 39
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Job Description
The Data Products Team builds and certifies the data products that power outage management and reliability reporting. The team owns the full data lifecycle, from raw source feeds to validated, stakeholder-ready outputs.
We’re looking for a hands-on Data Engineer to build and maintain ETL pipelines, implement data quality validations, and support the delivery of certified, versioned data products. You will work closely with the team and operational stakeholders to ensure data accuracy, reliability, and readiness for downstream reporting and business use.
Responsibilities
Build and maintain scalable ETL pipelines using AWS Glue, Spark, and Athena to process modem telemetry, outage events, and customer impact data.
Develop and manage daily data quality checks, including SQL validations, threshold-based alerts, and row-count monitoring.
Investigate data anomalies such as nulls, duplicates, missing intervals, and unexpected data distributions, resolving issues before they affect downstream systems.
Integrate data from multiple upstream systems, including AOM, IPDR, Scope, CARS, IRIS, and Gisual, to produce unified, validated datasets.
Support data product certification by validating outputs and ensuring they meet established quality standards before stakeholder delivery.
Coordinate versioned data product releases, including test case development, release notes, go/no-go decisions with end users, and patches through a structured release process.
Document data validation methodologies, pipeline behavior, and release processes.
Collaborate with data engineering teammates and BI and operational stakeholders throughout the data delivery lifecycle.
Qualifications
Strong proficiency in SQL, including window functions (LAG, PARTITION BY), grouping sets, null handling, and Athena-specific query patterns.
Experience with Python for scripting, automation, and data validation.
Hands-on experience with AWS data services, particularly Glue, Athena, S3, EMR, and Step Functions.
Experience using Spark for large-scale data processing, preferably on EMR.
Strong understanding of data quality and the ability to investigate anomalies, identify root causes, and determine when data does not look correct.
Experience validating data pipelines and ensuring data accuracy and consistency before downstream consumption.
Strong written communication skills, with the ability to document technical methodologies and coordinate effectively with teammates and stakeholders.
Nice to Have
Experience working with telecommunications or network operations data, including modem telemetry, outage records, or IPDR-style data feeds.
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.
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
Source details
Source notes
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- Pay
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- Location & working pattern
Guadalajara, Jal., Mexico
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