Data Engineer

Nexiva Inc; Montana; Ibrido; USD 120.000 - 160.000; Tempo pieno

Descrizione del lavoro

Nexiva INC. is seeking a Data Engineer in St. Louis, MO for a hybrid 12-month role.

You will design, develop, and deploy scalable data pipelines across on‑premises and cloud environments, leveraging Spark, Java/Scala, Hadoop, and AWS services. The position requires experience with data lakes/warehouses and strong collaboration with cross-functional teams. Responsibilities include end-to-end delivery, data quality controls, and mentorship of junior engineers in a fast-paced environment.

Competenze

• 7+ years delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
• Proven experience implementing multiple end-to-end data engineering projects in large-scale distributed environments.
• Hands-on experience migrating ETL and analytics workloads to cloud-native environments.

Mansioni

• Design, develop, test, and deploy high-quality, secure, scalable data pipelines using Apache Spark, Java/Scala across Hadoop and cloud-native object storage platforms.
• Build and maintain batch and near real-time data processing frameworks for petabyte-scale workloads.
• Develop reusable engineering components and frameworks that accelerate data product delivery while maintaining enterprise standards.
• Design and implement a build-once, run-anywhere architecture across on-premises and public clouds.
• Implement data lineage, metadata management, data cataloguing, data quality controls, and observability across the data ecosystem.
• Collaborate with architects and platform teams to establish scalable design patterns and best practices.
• Lead end-to-end development activities including requirements, design, coding, testing, deployment, and production support.
• Mentor junior engineers through code reviews, coaching, and best practices.
• Partner with product owners, analysts, and stakeholders to deliver high-quality solutions within timelines.
• Troubleshoot production incidents and perform root cause analysis for long-term remediation.
• Ensure compliance with client engineering, security, QA, and governance standards.
• Identify opportunities to improve performance, automation, monitoring, and process efficiency.
• Evaluate emerging data technologies and contribute to ideation and improvement initiatives.

Conoscenze

Data engineering

Cloud computing

Spark

Scala/Java

Hadoop

Airflow/NiFi

SQL

NoSQL

Mentoring

Problem solving

Strumenti

Apache Spark

Java/Scala

Hadoop

Airflow

NiFi

AWS

S3

SQL

NoSQL

Descrizione del lavoro

Hello There,

Hope you are doing well.

My name is Himanshu, and I serve as the Recruitment Manager at Nexiva INC. I am reaching out to share an excellent career opportunity for the role of \"Data Engineer\" with our esteemed client.

Job Description

Position : Data Engineer

Location : St. Louis. MO Hybrid

Duration : 12 Months (Hybrid role 3 days a week)

Recent Financial industry Domain must to have.

Key Responsibilities

Data Engineering & Development

• Design, develop, test, and deploy high-quality, secure, scalable, and resilient data pipelines using Apache Spark, Java/Scala across Hadoop and cloud-native object storage platforms.
• Build and maintain batch and near real-time data processing frameworks capable of supporting petabyte-scale workloads.
• Develop reusable engineering components and frameworks that accelerate data product delivery while maintaining enterprise standards.

Architecture & Platform Engineering

• Design and implement a \"build once, run anywhere\" architecture supporting seamless deployment across on-premises and public cloud environments without code changes.
• Implement data lineage, metadata management, data cataloguing, data quality controls, and observability capabilities across the data ecosystem.
• Collaborate with architects and platform teams to establish scalable design patterns and engineering best practices.

Cloud Modernisation

• Contribute to migration initiatives moving legacy ETL and data warehouse workloads from on-premises environments to cloud-native architectures.
• Leverage cloud services such as Amazon S3, EMR, Glue, and related data services to improve scalability, reliability, and operational efficiency.
• Drive adoption of modern lakehouse and distributed compute architectures.

Delivery & Technical Leadership

• Lead end-to-end development activities including requirement analysis, solution design, coding, testing, deployment, and production support.
• Mentor and guide junior engineers through code reviews, technical coaching, and engineering best practices.
• Partner with product owners, analysts, architects, and business stakeholders to deliver high-quality solutions within committed timelines.

Operational Excellence

• Troubleshoot complex production incidents and perform root cause analysis to identify and implement long-term remediation strategies.
• Ensure compliance with client engineering, security, quality assurance, and operational governance standards.
• Continuously identify opportunities to improve performance, automation, monitoring, and process efficiency.

Innovation

• Evaluate emerging data technologies and conduct proof-of-concept (POC) initiatives to determine their applicability within client data ecosystem.
• Contribute to engineering innovation and continuous improvement initiatives across the organisation.

Qualifications

Required Experience

• 7+ years of experience delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
• Proven experience implementing multiple end-to-end data engineering projects within large-scale distributed computing environments.
• Hands-on experience migrating ETL and analytics workloads from on-premises platforms to cloud-native environments.

Technical Expertise

• Strong development experience using:Apache Spark, Scala or Java, Hadoop ecosystem technologies, Object Storage platforms
• Experience building orchestration and workflow solutions using: Apache Airflow/ Apache NiFi and Similar enterprise scheduling frameworks
• Strong SQL expertise and experience with Relational and NoSQL database technologies: Oracle/ SQL Server, Cassandra, Dynamo DB etc.
• Working knowledge of cloud platforms, preferably AWS: Amazon S3, EMR, AWS Glue, Cloud-native data services

Professional Skills

• Strong analytical and problem-solving capabilities.
• Experience operating within Agile delivery environments.
• Excellent written and verbal communication skills.
• Proven ability to collaborate within geographically distributed and matrix-based teams.
• Self-starter with strong ownership, accountability, and execution focus.
• Ability to learn emerging technologies quickly and apply them effectively to business challenges.

Thanks & Regards

Himanshu Sharma

Recruitment Manager

Email: [e-mail]

LinkedIn: https://www.linkedin.com/in/himanshustaffingexpert/