FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and operating data pipelines using Spark, Java, and Python, with a strong focus on data quality, observability, and governance. Proficient in applying software engineering principles and collaborating with data scientists and ML engineers to enhance data platform capabilities.
Highest-signal resume keywords
Java ProficiencyPython ProficiencySpark ExpertiseData Quality GovernanceMLOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringBatch ProcessingStreaming ProcessingETL/ELT Pipeline DesignData ModelingDistributed SystemsSystem DesignCode Review StandardsTesting StrategyWorkflow Orchestration
Soft Skills
Technical JudgmentOwnershipAutonomyMentoring
Tools & Technologies
HadoopHDFSHiveKafkaAirflowDelta LakeBigQueryDatabricksKubernetesCI/CD
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Engineering
Industry Keywords
Big DataCloud TechnologiesAIGenAIAgentic Workflows
Tech Stack
Tools & technologiesAirflowBigQueryCloudDistributed SystemsETLHadoopHDFSJavaKafkaKubernetesMicroservicesPythonScalaSparkC++Go
About the role
Key responsibilities & impact- Design, build, and operate batch and streaming data pipelines using Spark, Java, and Python
- Apply software engineering fundamentals including clean architecture, automated testing, CI/CD, and code review discipline
- Apply system design and low-level design rigor to data and platform problems
- Contribute to services, APIs, and distributed systems in the broader platform codebase
- Apply AI, GenAI, and agentic capabilities to data platform problems
- Partner with data scientists and ML engineers on feature pipelines, model-serving data paths, and MLOps infrastructure
- Own data quality, observability, and governance for pipelines and datasets
- Participate in architecture and design reviews across data and platform engineering
- Provide technical judgment in design and code reviews, mentor early-career engineers, and improve engineering quality
- Stay current on Big Data, cloud, and AI/agentic technologies and propose improvements to reliability, productivity, and business value
Requirements
What you’ll need- 5+ years of professional software engineering experience with hands-on data engineering at scale
- Strong proficiency in Java and Python
- Strong working knowledge of Spark for distributed data processing
- Operational Excellence and Engineering Excellence mindset, including SLO/SLA ownership, incident management, blameless post-incident reviews, reliability and quality metrics, and continuous improvement
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- Solid experience with Spark, Hadoop/HDFS, Hive, Kafka, workflow orchestration such as Airflow, batch and streaming processing, and large-scale data transformation
- Experience with data modeling, ETL/ELT pipeline design, data quality and observability, data governance, and lakehouse architectures such as Delta Lake, BigQuery, and Databricks
- Hands-on experience integrating model APIs and GenAI/LLM tooling, building or operating agentic workflows, embeddings/vector search, and MLOps practices
- Working literacy in microservices, API design, Kubernetes or equivalent orchestration, CI/CD, and cloud-native practices
- Distributed systems fundamentals including event-driven patterns, service contracts, asynchronous processing, and fault tolerance at scale
- System design and low-level design skills, including evaluation of trade-offs, failure modes, scalability, and cost
- Strong software engineering craftsmanship, including testing strategy, code review standards, design patterns, and system design for high-throughput data systems
- Ability to translate data/business problems into technical execution plans
- Strong ownership, technical judgment, and autonomy in a 0-to-1 environment
- Additional experience with Go, C++, or Scala is a plus
Benefits
Comp & perks- Incentive awards for performance
- Maternity and parental leave
- PTO
- Health benefits
- Flexibility for associates to manage their personal lives
- Compensation package