Data Engineer

• Implement robust data infrastructure, platforms, and solutions by ensuring the delivery of timely data load and jobs tailored to their unique needs.
• Collaborate effectively with the data team by prioritizing a service-oriented approach and quick response times.
• Strong adherence to high data quality standards, KPI certification methods, and engineering best practices.
• Approach reporting platforms and analytical processes with innovative thinking, considering the evolving demands of the business.
• Master the different data tools, clouds (AWS, GCP) and data engineering practices in the CDI ecosystem.
• Continuously improve reporting workflows and efficiency, harnessing the power of automation whenever feasible.
• Enhance the performance, reliability, and scalability of storage and compute layers of the data lake.

About You

• 2+ years of hands-on experience in data engineering and/or software development.
• Skilled in programming languages like Python, Spark & SQL
• Comfortable using BI tools like Tableau, Preset, and so on
• Experience in managing large-scale data sets, handling Terabytes of data and billions of records effectively (across structured and unstructured datasets)
• Good understanding of implementing compute and orchestration tools like Databricks, Airflow, Talend, and others.
• Good experience leveraging AWS services including EMR Spark, Redshift, and S3 among others. Nice to have exposure to GCP services like BigQuery, Google Storage, Looker, Google Analytics, and so on
• Nice to have experience in event data collection tools such as Snowplow, Segment, Google Tag Manager, Tealium, or mParticle,
• You holds a Bachelors degree in Computer Science, Information Systems, or a related field, providing a strong foundational knowledge