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Ethereum Technologies is seeking a senior Data Engineer to design, build, and optimize scalable data platforms and pipelines supporting enterprise analytics. You will work with Python, SQL, PySpark, and cloud services (AWS/Azure/GCP), implement ETL/ELT, data governance, and collaborate with data scientists, analysts, and stakeholders.
The role emphasizes data quality, performance, and secure data access in a fast-paced Agile environment.
US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other
The Data Engineer will build, maintain, and optimize scalable data platforms and pipelines to support enterprise analytics and business intelligence initiatives. This role focuses on data integration, transformation, processing, and cloud-based data architecture while ensuring data quality, reliability, and performance.
Strong programming experience with Python, SQL, and PySpark.
Hands-on experience with ETL/ELT development and data pipeline architecture.
Knowledge of Apache Spark, Hadoop, and distributed data processing.
Experience with cloud data platforms such as AWS, Azure, or Google Cloud.
Familiarity with Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, or AWS Glue.
Strong understanding of relational and NoSQL databases.
Knowledge of data modeling, data warehousing, and dimensional modeling.
Experience with Kafka or other streaming technologies is preferred.
Familiarity with Git, Docker, Kubernetes, and CI/CD pipelines.
Understanding of data governance, metadata management, and data security.
Design, develop, and maintain scalable ETL/ELT data pipelines.
Build data ingestion and transformation workflows from multiple sources.
Process large datasets using Python, SQL, PySpark, and Spark.
Develop and optimize data warehouse and lakehouse solutions.
Implement data validation, reconciliation, and quality checks.
Integrate structured and unstructured data from enterprise systems.
Optimize query performance and improve data pipeline efficiency.
Monitor pipeline execution, troubleshoot failures, and resolve data issues.
Implement data security, governance, and access-control standards.
Collaborate with data scientists, analysts, architects, and business stakeholders.
5+ years of experience in data engineering or big data development.
Strong hands‑on experience building and supporting production data pipelines.
Experience working with cloud-based data platforms and enterprise databases.
Understanding of distributed computing and data processing frameworks.
Strong analytical, debugging, and problem-solving abilities.
Experience working in Agile development environments.
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field.
Master's degree is preferred.
Certifications in AWS, Azure, Google Cloud, Snowflake, or Databricks are an advantage.
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.