Data Engineer

Resonate

. Design, develop, and maintain ETL/ELT pipelines powering the Resonate business using Spark and Scala on AWS EMR .

Posted 11/4/2026full-timeRemote • United StatesMid-LevelSenior💰 $120,000 - $155,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining ETL/ELT pipelines using Spark and Scala on AWS, with a strong focus on performance tuning and data quality management. Proficient in leveraging generative AI tools for data engineering tasks and possesses solid experience in big data ecosystems.

Highest-signal resume keywords

Spark Application TuningETL/ELT Pipeline DevelopmentAWS EMR and S3Data Quality ManagementGenerative AI in Data Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SparkScalaDataFrame APIDataset APIRelational Database ManagementBig Data DebuggingData StructuresData ModelingProbabilistic Data StructuresHigh Cardinality Data Systems

Soft Skills

Problem-SolvingCollaborationCommunication

Tools & Technologies

AWS EMRSnowflakeGrafanaKafkaHadoopElastic StackDocker

Certifications & Qualifications

Bachelor's Degree in Computer ScienceComputer Engineering

Industry Keywords

ETLELTBig DataData EngineeringSoftware Development Lifecycle

Tech Stack

Tools & technologies

AWSDockerETLGrafanaHadoopKafkaScalaSnowflakeSpark

About the role

Key responsibilities & impact

Design, develop, and maintain ETL/ELT pipelines powering the Resonate business using Spark and Scala on AWS EMR
Work with terabyte-scale datasets across S3 and Snowflake
Tune multi-terabyte and petabyte-scale Spark applications for performance and cost
Debug production-scale big data problems
Partner with senior engineers and product management to take product requests from design and planning through production
Monitor pipeline health in Grafana
Track down and resolve data quality issues at their source
Write clean, testable code with thorough unit and integration tests
Use Gen AI tools across pipeline development, monitoring, and daily engineering work
Participate in code reviews, technical design discussions, and sprint planning
Contribute to architecture decisions
Support production operations, including on-call rotation and incident response

Requirements

What you’ll need

Around five years or more of professional experience in software engineering, data engineering, or a closely related field
At least three years hands-on with Spark and Scala, specifically the DataFrame and Dataset APIs
Proven experience tuning Spark applications at multi-terabyte or petabyte scale
Real debugging and problem-solving experience in the big data ecosystem, including production failures
Solid relational database experience
Working knowledge of AWS (EMR, S3, Lambda), Kafka, Snowflake, Grafana, Hadoop, Elastic Stack, and Docker
Strong grasp of the full software development lifecycle, from exploration and design through production delivery
Good instincts on solution architecture, data structures, and data modeling
Enthusiasm for using generative AI to accelerate data engineering work
Hands-on experience building and maintaining big data pipelines with Gen AI
Experience using probabilistic data structures
Track record of implementing high cardinality data systems at scale
Bachelor's degree in computer science, computer engineering, or equivalent experience is a strong signal

Benefits

Comp & perks

Annual bonus program tied to company performance
Medical, dental, and vision coverage, including HSA
Company-paid disability and life insurance with a life insurance buy-up option
401(k) with company match
Flexible PTO plus 10 paid holidays
Paid parental leave
Access to wellbeing and employee assistance programs, including free and unlimited access to 20+ health professionals and wellbeing coaches for you and your family members
Remote-first environment with genuine flexibility
Occasional travel for company and client events