Accolite
Data Engineer
Job Description
Key Responsibilities:
●Data Architecture & Engineering:
○Design and implement scalable data architectures leveraging BigQuery, Iceberg,
Starburst, and Trino.
○Develop robust, high-performance ETL/ELT pipelines to process structured and
unstructured data.
○Optimize SQL queries and data processing workflows for efficient analytics and
reporting.
●Cloud & Big Data Infrastructure:
○Build and maintain data pipelines and storage solutions using Google Cloud
Platform (GCP) and BigQuery.
○Implement best practices for data governance, security, and compliance within
cloud-based environments.
○Optimize data ingestion, storage, and query performance for high-volume and
high-velocity datasets.
●Data Processing & Analytics:
○Leverage Apache Iceberg for large-scale data lake management and
transactional processing.
○Utilize Starburst and Trino for distributed query processing and federated data
access.
○Develop strategies for data partitioning, indexing, and caching to enhance
performance.
●Collaboration & Integration:
○Work closely with data scientists, analysts, and business stakeholders to
understand data needs and requirements.
○Collaborate with DevOps and platform engineering teams to implement CI/CD
pipelines and infrastructure-as-code for data workflows.
○Integrate data from multiple sources, ensuring data integrity and accuracy across
systems.
●Performance Optimization & Monitoring:
○Monitor, troubleshoot, and optimize data pipelines for efficiency, scalability, and
reliability.
○Implement data quality frameworks and automated validation checks to ensure
consistency.
○Utilize monitoring tools and performance metrics to proactively identify
bottlenecks and optimize queries.
Qualifications:
●Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering,
Information Systems, or a related field.
●Experience:
○4+ years of experience in data engineering, with expertise in SQL, BigQuery, and
GCP.
○Strong experience with Apache Iceberg, Starburst, and Trino for large-scale data
processing.
○Proven track record of designing and optimizing ETL/ELT pipelines and
cloud-based data workflows.
●Technical Skills:
○Proficiency in SQL, including query optimization and performance tuning.
○Experience working with BigQuery, Google Cloud Storage (GCS), and GCP data
services.
○Knowledge of data lakehouse architectures, data warehousing, and distributed
query engines.
○Hands-on experience with Apache Iceberg for managing large-scale
transactional datasets.
○Expertise in Starburst and Trino for federated queries and cross-platform data
access.
○Familiarity with Python, Java, or Scala for data pipeline development.
○Experience with Terraform, Kubernetes, or Airflow for data pipeline automation
and orchestration.
Preferred Skills:
●Understanding of machine learning data pipelines and real-time data processing.
●Experience with data governance, security, and compliance best practices.
●Exposure to Kafka, Pub/Sub, or other streaming data technologies.
●Familiarity with CI/CD pipelines for data workflows and infrastructure-as-code.
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