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Data Engineer

Trustech • Full-time • Sunnyvale, CA, US • 1d ago

NOTE: Candidates requiring sponsorship now or in the future (including CPT/OPT) cannot be considered for this job

This is a Full-Time, direct hire position. NO C2C

This role will start On-Site in the South Bay area, transitioning to Hybrid

Data Engineer

Overview:

Out client is seeking an experienced Data Engineer to architect, build, and refine high-performance data systems. The ideal candidate will have expertise in cloud-based platforms, large-scale data processing, and modern storage solutions. This role involves designing and implementing robust data pipelines, optimizing existing infrastructure, and ensuring the reliability of data solutions used for advanced analytics and applications. Success in this position requires close collaboration with cross-functional teams, from gathering requirements to validating and delivering production-ready solutions.

Key Responsibilities:

Improve and expand current data workflows and models to integrate additional sources and address evolving business needs.
Create and implement new data architectures, defining schemas and transformation processes using advanced ETL tools and frameworks.
Design and build new pipelines and backend logic for emerging use cases, leveraging languages such as Python, C++, or TypeScript.
Employ a range of AWS services—such as S3, Glue, Athena, Redshift, Kinesis, EMR, DynamoDB, and Terraform—to support scalable data operations.
Integrate and process data from varied sources including databases, APIs, raw datasets, and streaming sensor data.
Work closely with engineers, data scientists, and operational teams to translate user requirements into high-quality, scalable solutions.
Establish and maintain monitoring and validation processes to safeguard data accuracy and consistency.

Qualifications:

Bachelor’s or Master’s degree (or equivalent experience) in Computer Science, Data Engineering, or a related discipline.
At least five years of experience building scalable backend pipelines and/or data platforms with measurable performance improvements.
Strong command of SQL, NoSQL, and associated database technologies.
Hands-on programming expertise with Python, C++, TypeScript, or related languages.
Skilled in ETL pipeline design and implementation.
Experience working with internal and external APIs for data access and integration.
Proficient in profiling, optimizing, and tuning large-scale datasets.
Familiar with performance monitoring and observability tools.
Knowledge of ELK (Elasticsearch, Logstash, Kibana) or similar platforms.
Understanding of real-time or streaming technologies such as Kafka or Kinesis.

Preferred Skills:

Background in building visual analytics with tools like Tableau, Looker, or Kibana.
Experience architecting data lakes or enterprise-scale data warehouses.
Familiarity with governance and lineage tracking platforms.
Exposure to AWS managed data services and real-time data processing systems.
Strong technical communication skills with the ability to document systems clearly.
Enthusiasm for innovation and the future impact of data-driven solutions.