Senior Data Engineer

Klaxontech Inc
Jersey City, NJ, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$83,200.0 - $104,000.0
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence Airflow Amazon Web Services Amazon S3 Apache HTTP Server Microsoft Azure Big Data BigQuery Cloud Computing Cloud Storage Information Systems
+62 more
Continuous Integration Data Architecture Data Cleansing Information Engineering Data Governance Extract Transform Load (ETL) Data Systems Data Vault Modeling Data Warehousing DevOps Dimensional Modeling Distributed Computing Environment Distributed Systems Data Flow Control Github Apache Hadoop Python (Programming Language) Machine Learning MongoDB Neo4j NoSQL Power BI Azure Active Directory Standard Sql Cloudera Azure Data Lake Shell Script Systems Integration Scripting Google Cloud Data Ingestion Microsoft Power Automate Azure Data Factory Snowflake Grafana Apache Spark Microsoft Fabric Data Lakes Pyspark Kubernetes Information Technology Collibra Cassandra AWS Glue Data Analytics Star Schema Real Time Data Apache Kafka Spark Streaming Data Management Machine Learning Operations Presto Terraform Stream Processing Azure Synapse Analytics Stream Analytics Looker Analytics Data Pipelines Serverless Computing Docker Jenkins Databricks

Job description

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., * 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

Requirements

Do you have experience in Terraform?, Do you have a Bachelor’s degree?, * 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

Benefits & conditions

$40 - $50 an hour - Contract

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