Data Engineer

BusPatrol

. Build and maintain data infrastructure supporting reporting, analytics, and data science initiatives .

Posted 11/6/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining data infrastructure, creating data pipelines in AWS, and managing the data ecosystem from ingestion to analytics. Proficient in SQL, Python, and dimensional data modeling, with a strong focus on automation and optimization.

Highest-signal resume keywords

Data Pipeline DevelopmentAWS Services (Redshift, EC2, EMR/Spark, S3, Lambda, Glue)SQL (Redshift, MySQL, PostgreSQL, Snowflake, Databricks)Python DevelopmentData Lake Architecture

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringDatabase EngineeringBusiness IntelligenceETL ProcessesSchema DesignDimensional Data ModelingAPI DesignData VisualizationMachine LearningGIS

Soft Skills

Analytical AbilityProblem-SolvingCollaborationCommunicationStrategic Thinking

Tools & Technologies

TableauJIRA

Industry Keywords

Data InfrastructureData EcosystemData ScienceReportingAnalytics

Tech Stack

Tools & technologies

Amazon RedshiftAWSEC2ETLMySQLPostgresPythonSnowflakeSparkSQLTableau

About the role

Key responsibilities & impact

Build and maintain data infrastructure supporting reporting, analytics, and data science initiatives
Create and orchestrate data pipelines in AWS using Redshift, EC2, EMR/Spark, S3, Lambda, Glue, and related services
Manage the data and analytics ecosystem from ingestion and ETL through aggregate tables
Design and implement internal data pipeline processes and improvements through automation, optimization, and infrastructure redesign
Develop scripts for scheduling data ingestion and synchronization
Implement backend logic to create data marts for stakeholder self-service
Partner with data architects to build metrics-as-code frameworks and optimize data search and retrieval
Troubleshoot production data jobs and processes, resolve data quality issues, and improve pipeline performance
Build complex datasets with multidimensional relationships for functional and non-functional business requirements
Develop system integrations to ensure seamless data flow
Collaborate with business stakeholders, data architects, and data team colleagues
Responsibly leverage AI while maintaining ownership of outputs, mastering the codebase, and preventing software bloat

Requirements

What you’ll need

Bachelor’s degree or higher in a quantitative or technical field (e.g., Computer Science, Statistics, Engineering) or equivalent experience
5+ years of experience in data engineering, database engineering, business intelligence, or business analytics
5+ years of SQL experience for reporting and transformation, including Redshift, MySQL, PostgreSQL, Snowflake, or Databricks
4+ years of Python experience, including class development, within a Git-managed CI/CD team development environment
4+ years of experience with schema design and dimensional data modeling
Experience with Data Lake architectures and integrating structured and unstructured data into unified models
Experience with API design and development of RESTful web services
Ability to define and align to a long-term vision, diagnose issues independently, and work with code, data, and logs
Analytical ability to structure and process qualitative data and draw insightful conclusions
Experience with data science and machine learning (a plus)
Experience with GIS (a plus)
Data visualization experience with tools such as Tableau (a plus)
Experience with JIRA (preferred)
Strong interest in understanding business strategy and how data engineering contributes to organizational goals

Benefits

Comp & perks

Remote work arrangement stated in the description
Travel less than 5%