Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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У роли понятный фокус на инженерии данных, актуальный стек AWS и Spark и конкретные возможности для обучения, но зарплата не указана, а формат сервисной компании может означать работу под запросы клиентов.
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Зарплата не указанаКлиентские проектыАктуальный стекПонятные задачиПоддержка развития
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Engineer (AWS/Spark): Building and certifying scalable ETL pipelines and validated data products for outage management and reliability reporting with an accent on data quality, AWS data services, and large-scale processing. Focus on investigating anomalies, coordinating versioned releases, and ensuring accurate, stakeholder-ready datasets.
Location: Hybrid in Guadalajara, Jalisco, Mexico
Company
hirify.global is an AI services provider that combines data science, artificial intelligence, technology, and human expertise to create data-driven solutions for clients.
What you will do
Build and maintain scalable ETL pipelines with AWS Glue, Spark, and Athena for modem telemetry, outage events, and customer impact data.
Develop daily data quality checks using SQL validations, threshold-based alerts, and row-count monitoring.
Investigate nulls, duplicates, missing intervals, and unexpected data distributions, resolving issues before downstream impact.
Integrate data from AOM, IPDR, Scope, CARS, IRIS, and Gisual into unified, validated datasets.
Support data product certification and coordinate versioned releases, including test cases, release notes, go/no-go decisions, and patches.
Document validation methods and pipeline behavior while collaborating with data engineering, BI, and operational stakeholders.
Requirements
Strong SQL proficiency, including window functions, grouping sets, null handling, and Athena-specific query patterns.
Experience with Python for scripting, automation, and data validation.
Hands-on experience with AWS Glue, Athena, S3, EMR, and Step Functions.
Experience using Spark for large-scale data processing, preferably on EMR.
Strong understanding of data quality, anomaly investigation, root-cause analysis, and pipeline validation.
Strong written communication skills for technical documentation and stakeholder coordination.
Nice to have
Experience with telecommunications or network operations data, including modem telemetry, outage records, or IPDR-style feeds.
Culture & Benefits
Access to AWS, Databricks, Snowflake, and AI learning opportunities, certifications, study plans, and courses.
Access to Udemy Business and English lessons.
Mentoring programs and career development plans.
Flexible working options.
Company-provided equipment and rewards for personal milestones.
Opportunities to attend industry conferences and meet clients; benefits may vary by LATAM location.
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