Data Engineering Professional, Mexico
hace 3 semanas
Wizeline is a global digital services company that helps mid-size to Fortune 500 companies build, scale, and deliver high-quality digital products and services.
We thrive in solving our customer's challenges through human-centered experiences, digital core modernization, and intelligence everywhere (AI/ML and data). Our goal is to help them succeed in building digital capabilities that bring technology to the core of their business.
Your Key ResponsibilitiesThis job posting is for a Data Engineer to join our team. Your day-to-day work will involve:
- Collaborating with product owners, report developers, product analysts, architects, and business partners to design and implement product features within an Agile/Scrum methodology.
- Designing and implementing data platforms for large-scale, high-performance, and scalable requirements, integrating data from several sources, and managing structured and unstructured data while melding existing warehouse structures.
- Analyzing, diagnosing, and identifying bottlenecks in data workflows.
- Participating in demos to clients and requirements elicitation and translation to systems requirements (functional and nonfunctional).
- Continuously monitoring, refining, and reporting on the performance of data management systems.
To be successful in this role, you must have:
- Strong programming skills with Python.
- Solid experience with Spark.
- Experience working with SQL in advanced scenarios that require heavy optimization.
- 7+ years of experience with large-scale data engineering with an emphasis on analytics and reporting.
- 3+ years of experience developing on Hadoop-like ecosystems.
- Experience building cloud-scalable, real-time, and high-performance data lake solutions.
- Proficiency in designing and implementing ETL processes, dealing with big volumes of data (terabytes of data requiring distributed processing).
- Experience developing solutions within cloud services (AWS, GCP, or Azure).
- Experience with NoSQL databases such as Apache HBase, MongoDB, or Cassandra.
- Experience in data streams processing technologies including Kafka, Spark Streaming, etc.
- Advanced English level.
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