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Senior Data Engineer
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Klaxon Technolgies
Remote
$93,600 Salary, Full-Time
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Job Description
Senior Data Engineer Klaxon Technolgies Jersey City, NJ Job Details Contract $40 - $50 an hour 1 day ago Benefits Health insurance Qualifications Function as a Service (FaaS) Data model design Athena Looker Data quality checks Commercial use (data warehousing systems) Databricks Data visualization software proficiency Computer Science Azure Function proficiency Cassandra SQL databases Infrastructure as Code (IaC) Data quality assurance Spark GitHub Actions MongoDB AI platforms (beyond public GPTs) Object storage systems Schema design Snowflake SQL Azure Synapse Analytics Machine learning cloud services IT monitoring tools Docker Bachelor's degree Data integrity process (data warehousing) Azure DevOps proficiency AWS Glue Full Job Description Job Title Senior Data Engineer - Multi-Cloud Platform (Azure / AWS / GCP) Experience 10+ Years Location Remote / Hybrid / Onsite Employment Type Contract (W2 Only) Job Summary We are seeking a highly skilled and experienced Senior Data Engineer with 10+ years of expertise in designing, developing, and optimizing enterprise-scale data platforms across Azure, AWS, and GCP cloud ecosystems. The ideal candidate should possess strong hands-on experience with modern data engineering frameworks, cloud-native services, big data technologies, real-time data processing, data warehousing, and AI-ready analytics platforms. The candidate will play a key role in building scalable, secure, and high-performance data pipelines, enabling advanced analytics, reporting, machine learning, and enterprise data modernization initiatives. Key Responsibilities Design, build, and maintain scalable ETL/ELT pipelines across multi-cloud platforms. Develop enterprise-grade data solutions using Azure, AWS, and GCP services. Build and optimize modern Lakehouse architectures using Databricks, Microsoft Fabric, Synapse, Snowflake, and BigQuery. Implement batch and real-time data ingestion pipelines using Kafka, Spark Streaming, Event Hub, Kinesis, and Pub/Sub. Create reusable and automated workflows using orchestration tools such as Airflow, ADF, Glue Workflows, and Fabric Pipelines. Optimize cloud data warehouse performance, partitioning strategies, indexing, and cost management. Work closely with Data Scientists, BI teams, Architects, and Business stakeholders. Implement data governance, cataloging, lineage, security, and compliance standards. Build CI/CD-enabled deployment frameworks for data engineering solutions. Monitor and troubleshoot large-scale distributed data processing systems. Support AI/ML data preparation pipelines and GenAI-enabled analytics initiatives. Lead architecture discussions and mentor junior engineers. Required Skills & TechnologiesCloud Platforms Microsoft Azure Amazon Web Services (AWS) Google Cloud Platform (GCP) Azure Stack Microsoft Fabric Azure Synapse Analytics Azure Data Factory (ADF) Azure Databricks Azure Data Lake Storage (ADLS) Azure Event Hub Azure Functions Power BI Purview AWS Stack AWS Glue Redshift EMR Athena Lambda Kinesis S3 Lake Formation Step Functions GCP Stack BigQuery Dataflow Dataproc Pub/Sub Composer Cloud Storage Vertex AI Looker Big Data & Modern Data Tools Apache Spark PySpark Scala Hadoop Ecosystem Kafka Delta Lake Iceberg Hudi dbt Snowflake Trino Presto Programming & Scripting Python SQL Scala Shell Scripting Orchestration & DevOps Apache Airflow Terraform Docker Kubernetes Jenkins GitHub Actions Azure DevOps CI/CD Pipelines Data Modeling & Warehousing Dimensional Modeling Data Vault Star/Snowflake Schema Lakehouse Architecture Medallion Architecture Monitoring & Governance Microsoft Purview Collibra Apache Atlas Data Quality Frameworks Observability Tools Preferred Qualifications Bachelor's or Master's degree in Computer Science, Information Systems, or related field. Cloud certifications in Azure, AWS, or GCP are highly preferred. Experience working in Banking, Healthcare, Retail, Telecom, or Insurance domains. Strong understanding of AI/ML-ready data platforms and GenAI integrations. Experience with real-time analytics and streaming architectures. Exposure to modern semantic models and Fabric OneLake concepts. Nice to Have Experience with AI-powered analytics platforms Knowledge of Microsoft Copilot / Fabric AI capabilities Exposure to MLOps platforms Experience with OpenAI integrations and vector databases Hands-on with Neo4j, MongoDB, Cassandra, or other NoSQL databases Experience implementing data mesh architecture Key Traits Strong problem-solving and analytical skills Excellent communication and stakeholder management Ability to work in fast-paced Agile environments Leadership and mentoring capabilities Strong understanding of enterprise-scale distributed systems