Senior Data Engineer

Tiger Analytics

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

Posted 10/10/2026full-timeRemote • Texas • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in designing and maintaining scalable data pipelines using Databricks, Apache Spark, Python, and Scala, with a strong focus on ETL/ELT processes and performance optimization. Collaborates effectively with cross-functional teams to deliver reliable data solutions while ensuring data accuracy and consistency.

Highest-signal resume keywords

DatabricksApache SparkPythonScalaETL/ELT Processes

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringPerformance TuningSQLData TransformationDebuggingTroubleshootingData Management

Soft Skills

Analytical SkillsProblem-SolvingCollaboration

Tools & Technologies

HadoopControl-M

Industry Keywords

Big Data TechnologiesData PipelinesWorkflow Orchestration

Tech Stack

Tools & technologies

ApacheETLHadoopPythonScalaSparkSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources
Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data
Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability
Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines
Troubleshoot job failures, resolve data pipeline issues, and ensure timely completion of scheduled workloads
Implement data validation, error handling, and quality checks to ensure data 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 deployment procedures
Support production deployments, incident resolution, and ongoing maintenance of data engineering solutions

Requirements

What you’ll need

8+ years of overall Data Engineering experience
Strong hands-on experience with Databricks and Apache Spark
Proficiency in Python and Scala for data processing and application development
Hands-on experience with Hadoop and big data technologies
Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management
Strong understanding of ETL/ELT processes, data transformations, and distributed data processing
Experience in performance tuning, debugging, troubleshooting, and production support
Strong SQL skills and understanding of data management concepts
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
Continuous learning and hands-on exposure to emerging technologies
Opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms
Collaboration with global AI, data, engineering, and consulting talent
Opportunities to lead strategic engagements and grow strategic client partnerships