10 часов назад
Data Engineer & Analytics
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer & Analytics (Data Warehousing/Analytics): Building scalable data pipelines and analytics engines that help internal stakeholders derive insights from warehouse data with an accent on data integration, documentation, and data quality. Focus on solving complex multi-system integrations, designing robust SQL and Python solutions, and supporting cloud-based data platforms.
Location: Jakarta, Indonesia
Company
is hiring for a role focused on internal data warehouse, analytics, and business intelligence solutions.
What you will do
- Design and develop scalable business data solutions across the full data supply chain.
- Build data pipelines and analytics engines that enable internal stakeholders to explore warehouse data and generate insights.
- Create and review documentation including data models, data dictionaries, business glossaries, process and data flows, and architecture diagrams.
- Solve complex data integrations across multiple systems.
- Collaborate with management, business partners, analysts, developers, architects, and engineers to improve data quality.
Requirements
- 1–3 years of relevant experience in data engineering, data warehousing, business intelligence, or analytics.
- Strong SQL skills across relational databases and OLAP platforms such as MySQL, PostgreSQL, BigQuery, Redshift, or Oracle.
- Ability to write robust and scalable code in Python, Scala, or another scripting language.
- Knowledge of data warehousing concepts and technologies such as Redshift, Spark, Hadoop, and web services.
- Basic experience with cloud infrastructure using AWS, GCP, or Azure.
- Good communication skills in Bahasa and English, including the ability to explain technical concepts.
Nice to have
- Experience creating workable business dashboards.
- Experience with data science tools and technology stacks.
Culture & Benefits
- Task-oriented work requiring a careful, disciplined, and cautious approach.
- Opportunity to develop further in data engineering and business intelligence.
- Collaboration across Product, Engineering, Data, and business teams.
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