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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in designing and operating large-scale data pipelines using Java, Python, and Spark, while ensuring data quality, governance, and observability. Proficient in integrating AI capabilities and MLOps practices into data platforms, with a strong focus on operational and engineering excellence.
Highest-signal resume keywords
Java ProficiencyPython ProficiencySpark ExpertiseData 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 DesignDomain-Oriented DesignWorkflow OrchestrationData Quality
Soft Skills
Ownership MindsetTechnical JudgmentMentoringCollaborationProblem-Solving
Tools & Technologies
Hadoop/HDFSHiveKafkaAirflowKubernetesCI/CDCloud-Native PracticesGenAI/LLM ToolingMicroservicesObservability Tools
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Engineering
Industry Keywords
Big DataData PipelinesData GovernanceAI IntegrationAgentic Workflows
Tech Stack
Tools & technologiesAirflowCloudDistributed SystemsETLHadoopHDFSJavaKafkaKubernetesMicroservicesPythonSpark
About the role
Key responsibilities & impact- Design, build, and operate large-scale batch and streaming data pipelines using Spark, Java, and Python
- Apply clean architecture, automated testing, CI/CD, and code review discipline to data engineering
- Apply domain-oriented design, system design, and low-level design to data and platform problems
- Build and maintain services, APIs, and distributed systems supporting data pipelines
- Integrate AI, GenAI, and agentic capabilities into the data platform
- 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 and lead architecture and design reviews across data and platform engineering
- Set technical direction and best practices across teams; mentor engineers and influence data engineering standards
- Evaluate and adopt emerging Big Data, cloud, and AI/agentic technologies
Requirements
What you’ll need- 12+ years of professional software engineering experience with significant 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 skills, 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
- Deep 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
- 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
- Strong distributed systems fundamentals, system design, domain-oriented design, and low-level design skills
- Strong software engineering craftsmanship, including testing strategy, code review standards, and design patterns
- Ability to translate ambiguous data/business problems into technical execution plans
- Strong ownership mindset and technical judgment; comfortable operating with high autonomy
- Minimum qualification: Bachelor's degree and 5 years' experience in software engineering or related area, or 7 years' experience in software engineering or related area
- Must be able to work from the Bangalore/Chennai office for daily work
Benefits
Comp & perks- Incentive awards for performance
- Maternity and parental leave
- PTO
- Health benefits
- Flexibility for associates to manage their personal lives