Loker Lead Data Engineer NorthBay Solutions. NorthBay Solutions kembali membutuhkan calon pegawai untuk mengisi posisi sebagai Lead Data Engineer. NorthBay Solutions memberikan persyaratan, ketentuan dan spesifikasi pekerjaan sebagai Lead Data Engineer yang akan ditempatkan di Jakarta.

Loker Lead Data Engineer NorthBay Solutions Jakarta Desember 2024

Berikut ini adalah kualifikasi yang harus kalian penuhi untuk mendaftar Lead Data Engineer NorthBay Solutions Jakarta yang dibuka pada 11 Desember 2024 ini:

NorthBay Solutions, a premier US-based AWS partner with over a decade of experience serving clients globally, is seeking a passionate and experienced Tech Lead/Senior Architect to join our growing Data Engineering team.

About the Role: In this role, you will play a pivotal role in leading and architecting innovative solutions leveraging AWS Big Data technologies (e.g. S3, Redshift, EMR, Glue). You will collaborate closely with a global, multicultural team of Data Engineers and guiding project execution, ensuring technical excellence, and fostering a culture of continuous learning and supporting sales growth.

Key Qualifications & Required Knowledge:

• 10+ years of experience in technology, with a minimum of 6 years specifically focused on Data Engineering.
• Proven experience developing and implementing ETL pipelines on AWS that extract, transform, and load data for strategic business goals.
• Expertise in ETL Data Engineering using Python, Java, and Big Data technologies (Hadoop, PySpark, Spark SQL, Hive).
• Effective time management skills with a proven ability to manage and prioritize multiple project tasks.
• Experience creating and driving large-scale ETL pipelines in an AWS environment.
• Experience integrating data from diverse data sources.
• Strong software development and programming skills with a focus on data using Python/PySpark or Scala.

Preferred Qualifications (Nice to have):

• Experience with DevOps and CI/CD tools (Bitbucket, Bamboo, Ansible, Sonar, Atlassian suite).
• In-depth knowledge of core AWS services (IAM, CloudFormation, EC2, S3, EMR/Spark, Glue, Lambda, Athena, Redshift).
• Familiarity with popular data management tools (Data Lake, Databricks, Snowflake).
• Understanding of core data science concepts (statistics, modelling, algorithms).
• Experience with AWS AI/ML Services (SageMaker, Ground Truth) for building, training, and deploying machine learning models.
• Working knowledge of AWS infrastructure services (ECS, Cognito, CloudWatch, RDS: Postgres, API Gateway, Lambda) to support data engineering workflows and integrations.
• Acquainted with the value and evolution of Generative AI (GenAI) and its potential applications within the Big Data landscape.
• Basic familiarity with Amazon Q, a managed generative AI powered chat assistant, and Amazon Bedrock, a serverless service that hosts foundation models.

Technical Responsibilities:

• Design and develop innovative solutions leveraging Big Data technologies (Hadoop, Spark, etc.) to address complex data challenges.
• Architect and build highly scalable and distributed data systems on the AWS cloud platform.
• Design, develop, and manage robust ETL jobs and pipelines to ensure efficient data movement and transformation.
• Deploy production-ready data models, including data ingestion, configuration, resource management, and monitoring.

Leadership and Collaboration:

• Partner with sales to qualify opportunities, develop compelling technical solutions, and respond to RFPs.
• Serve as a thought leader, providing strategic guidance and mentoring junior team members as they leverage new data-driven solutions.
• Foster a culture of continuous learning and improvement by mentoring and training colleagues.
• Collaborate effectively to troubleshoot complex issues and provide timely guidance to team members.

Business Impact:

• Drive impactful business improvements by analysing data, identifying trends, and recommending process optimizations.

Additional qualities:

• Exceptional communication and English skills.
• Proven leadership.
• Client-facing expertise.
• Technological agility.
• Thrives in a fast-paced environment.
• Analytical & Detail-oriented.
• Self-driven leader.
• Team player.

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