תיאור המשרה
Company overview:
Cellebrite’s (Nasdaq: CLBT) mission is to enable its customers to protect and save lives, accelerate justice, and preserve privacy in communities around the world. Cellebrite is a global leader in Digital Intelligence solutions for the public and private sectors, empowering organizations to master the complexities of legally sanctioned digital investigations by streamlining intelligence processes. Trusted by thousands of leading agencies and companies globally, Cellebrite’s Digital Intelligence platform and solutions transform how customers collect, review, analyze, and manage investigative digital data in legally sanctioned investigations.
Position Overview:
As a Senior AWS Data Engineer you will play a critical role in shaping and delivering our data infrastructure and solutions on the AWS platform. You will collaborate with cross-functional teams to design scalable data architectures, develop efficient pipelines, and implement governance and security best practices.
Responsibilities:
- Design and implement scalable, secure, and cost-effective AWS-based data architectures, leveraging services such as S3, EMR, Glue, Lambda, Athena, DynamoDB, and Step Functions.
- Define best practices for data modeling, schema design, and optimization for performance and scalability.
- Data Pipeline Development, Build, optimize, and maintain ETL/ELT pipelines using tools like Glue, Spark (on EMR), and Lambda, Ensure pipelines can handle high volumes of structured, semi-structured, and unstructured data efficiently.
- Data Governance and Quality: Implement data governance practices, including data cataloging, lineage tracking, and quality monitoring. Establish data security standards using IAM, KMS, and other AWS security tools.
- Collaboration and Leadership: Work closely with product managers, data analysts, and software engineers to understand requirements and deliver end-to-end data solutions. Provide technical mentorship and contribute to team knowledge sharing.
- Operational Excellence: Monitor and troubleshoot data pipelines and infrastructure, ensuring high availability and reliability. Optimize costs and performance of AWS services.
- Minimum of 10 years in designing and developing data solutions, with significant experience on the AWS platform.
- Proficiency in AWS data services (e.g., S3, Glue, Redshift, Athena, DynamoDB, EMR, Lambda).
- Strong experience with big data frameworks (e.g., Apache Spark, Hadoop) and querying tools (e.g., SQL, Athena, Presto).
- Expertise in programming languages such as Python, Typescript, Scala, or Java.
- Hands-on experience with orchestration tools like Step Functions, Apache Airflow, or others.
- Data Governance: Knowledge of schema registries, data cataloging, lineage tools, and monitoring best practices.
Soft Skills:
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to mentor and guide junior developers.
- Preferred Qualifications:
- AWS Certifications such as AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Professional.
- Experience with DevOps practices, CI/CD pipelines, and Infrastructure as Code (e.g., CloudFormation, Terraform).
- Familiarity with third-party data tools and platforms like Databricks, Snowflake, or similar.
- Experience in implementing data democratization or self-service analytics solutions
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