
10.000+ funcionários
💰 $2.000.000 Venture Round em 2015-01
Escolher um parceiro digital vai além das capacidades — trata-se de colaboração e caráter.
🕒 Maio 15
🗣️🇺🇸🇬🇧 Inglês obrigatório
Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

10.000+ funcionários
💰 $2.000.000 Venture Round em 2015-01
Escolher um parceiro digital vai além das capacidades — trata-se de colaboração e caráter.
• Develop and maintain a comprehensive data architecture and cloud strategy that aligns with the organization's goals and needs. • Design, implement, and manage cloud-based data infrastructure on AWS, ensuring scalability, reliability, and cost-efficiency. • Utilize AWS services (S3, Glue, EMR, Redshift, Lambda, Kinesis, MWAA, etc.) to build and optimize data pipelines and storage solutions. • Champion the use of data lakehouse architecture and optimize its performance for analytical and operational workloads. • Identify the gaps and opportunities in the current system and suggest/implement to optimise the processes and costs. • Lead and guide data engineering teams to develop, maintain, and optimize ETL processes for data ingestion, transformation, and loading. • Implement real-time data processing solutions using technologies such as Apache Kafka and AWS Kinesis. • Collaborate with data scientists, business stakeholders and analysts to ensure data availability and quality, enabling effective analytics and reporting. • Leverage DBT for data modelling and transformation to support self-service analytics and data governance. • Architect and implement data integration solutions for API ingestion, enabling data from diverse sources to be captured, transformed, and ingested into our data lakehouse. • Utilize Airbyte and custom APIs to ensure efficient, reliable, and secure data transfers. • Manage data integration pipelines to support real-time and batch data processing. • Design, configure, and maintain workflow orchestration using Apache Airflow to automate ETL processes and data pipeline executions. • Monitor and optimize job scheduling, error handling, and performance of data workflows. • Implement data security protocols, access controls, and encryption to safeguard sensitive data, especially PIIs. • Ensure compliance with data privacy regulations and industry standards. • Collaborate with cross-functional teams to understand data requirements and provide data solutions to meet their needs. • Maintain comprehensive documentation for data engineering and data architecture processes and solutions. • Guide the team in setting up cloud Infra and automate using tools like terraform, cloud formation, Jenkins etc • Guide the operations team in setting up automated monitoring & alerts mechanism
• Bachelor's or higher degree in a relevant field. • 6+ years of proven experience in data engineering, cloud architecture, and AWS services. • Extensive knowledge of data lakehouse technologies, Hudi, DBT, Airbyte, Redshift, Glue, Kinesis and Apache Airflow. • Strong expertise in programming languages like SQL, Python and processing frameworks like PySpark • Strong expertise in real-time data processing. • Excellent problem-solving and analytical skills. • Strong communication and teamwork abilities. • Passion for Sports/Gaming/Entertainment is preferred
Candidatar-se🕒 Maio 15
10.000+ funcionários
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