Data Engineer

John Hancock
Boston, MA, United States
26 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours

Tech stack

Airflow Amazon Web Services Microsoft Azure Business Intelligence Development Big Data Information Systems Data Architecture Data Governance Extract Transform Load (ETL) Decision Support Systems DevOps Monitoring of Systems
+16 more
Python (Programming Language) Machine Learning NoSQL SQL Databases Data Ingestion Apache Spark Containerization Information Technology Integration Frameworks Cloudwatch Restful APIs Splunk Azure Synapse Analytics Data Pipelines Docker Databricks

Job description

Experteer Overview In this role, you will design, build, and optimize data pipelines to enable data-driven decision making. You will work within a cross-functional environment to migrate and modernize data architectures on cloud platforms, and to deliver scalable analytics solutions. You will partner with data scientists and business stakeholders to translate needs into robust data products and dashboards. This is a remote-friendly position at a leading financial services firm with a focus on governance, security, and reliability. Compensation / Benefits * Design, build and maintain ETL/ELT data pipelines for large datasets * Migrate legacy data architectures to Azure and AWS * Develop Spark-based pipelines via Databricks and Synapse * Automate data ingestion and transformation workflows with Airflow * Create interactive dashboards for stakeholders * Design and manage relational and NoSQL databases * Implement secure, compliant data pipelines with governance * Integrate data sources via REST APIs * Collaborate with data scientists to deploy ML models * Set up monitoring/alerting for data pipelines * Use Docker for deployment and ensure environment consistency * Identify and implement workflow efficiencies to reduce costs Tasks * Master’s degree in Computer Science, Electrical Engineering, Electronic Engineering, Information Systems or related field * 3 years of experience with Python, SQL, and ETL processes * 3 years of experience with AWS and Azure * 3 years of experience with Spark, Databricks and Synapse * 2 years of experience with Apache Airflow * 3 years of experience with Power BI and Tableau * 3 years of experience with SQL and NoSQL databases * 3 years of experience with data governance, compliance and security * 3 years of experience with REST APIs and integration frameworks * 3 years of experience with ML and predictive modeling * 3 years of experience with monitoring tools (Splunk, CloudWatch) * 2 years of experience with DevOps practices and containerization Key requirements * remote work * health and dental insurance * retirement savings plans * paid time off * holidays and sick leave * employee assistance programs

Requirements

firm via REST APIs * Collaborate with data scientists to deploy ML models * Set up monitoring/alerting for data pipelines * Use Docker for deployment and ensure environment consistency * Identify and implement workflow efficiencies to reduce costs Tasks * Master’s degree in Computer Science, Electrical Engineering, Electronic Engineering, Information Systems or related field * 3 years of experience with Python, SQL, and ETL processes * 3 years of experience with AWS and Azure * 3 years of experience with Spark, Databricks and Synapse * 2 years of experience with Apache Airflow * 3 years of experience with Power BI and Tableau * 3 years of experience with SQL and NoSQL databases * 3 years of experience with data governance, compliance and security * 3 years of experience with REST APIs and integration frameworks * 3 years of experience with ML and predictive modeling * 3 years of experience with monitoring tools (Splunk, CloudWatch) * 2 years of experience with aaaa

  • practices and containerization Key requirements * remote work * health and dental insurance * retirement savings plans * paid time off * holidays and sick leave * employee assistance programs

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Good distractions

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Maria Apazoglou · Coffee With Developers

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Establishing comprehensive monitoring and log management

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Correlating dispersed logs using structured request tracing

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Docker sandbox architecture and microVM environment integration

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