Senior Data Engineer

Tiger Analytics

. Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark.

Posted 10/15/2026full-timeRemote • New Jersey • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines using Azure data services, Python, and Scala, with a strong focus on ETL/ELT processes and data quality assurance. Proven ability to collaborate with cross-functional teams to deliver reliable data solutions while adhering to coding standards and CI/CD practices.

Highest-signal resume keywords

Azure Data FactoryApache SparkPythonETL/ELT ProcessesSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline ArchitectureData TransformationData Quality ChecksPerformance TuningDebuggingTroubleshootingBatch SchedulingWorkflow OrchestrationDistributed Data ProcessingData Validation

Soft Skills

Analytical SkillsProblem-SolvingCollaboration

Tools & Technologies

Azure DatabricksAzure Data Lake StorageHadoopControl-MCI/CD

Industry Keywords

Data EngineeringBig Data TechnologiesData IngestionData ProcessingVersion Control

Tech Stack

Tools & technologies

ApacheAzureETLHadoopPythonScalaSparkSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark.
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
Develop and optimize Spark applications to improve data processing performance, scalability, and reliability.
Work with Hadoop and related big data technologies where applicable.
Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery.
Implement data validation, error handling, and data quality checks to ensure accuracy and consistency.
Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions.
Follow coding standards, testing practices, version control, and CI/CD procedures.
Support production deployments, incident resolution, performance tuning, and ongoing maintenance of data engineering solutions.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
10+ years of overall Data Engineering experience.
Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage.
Proficiency in Python and Scala for data processing and application development.
Strong experience with Apache Spark and distributed data processing.
Hands-on experience with Hadoop and big data technologies.
Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture.
Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support.
Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
Familiarity with version control, CI/CD, and deployment practices.
Excellent analytical, problem-solving, and collaboration skills.

Benefits

Comp & perks

Medical, Dental, Vision
Retirement Accounts
Long and Short Term Disability
Life Insurance
HSA/FSA Accounts (USA)
Discretionary time-off
Strategic engagements involving enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes
Collaboration with AI, data, engineering, and consulting talent across geographies
Continuous learning and hands-on exposure to emerging technologies
Opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms
Opportunities to grow strategic client partnerships
Equal employment opportunities