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PySPark /Spark & Dataproc Senior Engineer

HoonarTek
Remote

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Job details

Full-time

Qualifications

CI/CD
Performance tuning
Business intelligence
Kubernetes
D3.js
Spark
Research
Ab Initio
SQL
Continuous integration
Scripting
Agile
Python
Debugging

Full job description

Hybrid, Bangalore, Pune

About Us

We empower enterprises globally through intelligent, creative, and insightful services for data integration, data analytics and data visualization.

Hoonartek is a leader in enterprise transformation, data engineering and an acknowledged world-class Ab Initio delivery partner.

Using centuries of cumulative experience, research and leadership, we help our clients eliminate the complexities & risk of legacy modernization and safely deliver big data hubs, operational data integration, business intelligence, risk & compliance solutions and traditional data warehouses & marts.

At Hoonartek, we work to ensure that our customers, partners and employees all benefit from our unstinting commitment to delivery, quality and value. Hoonartek is increasingly the choice for customers seeking a trusted partner of vision, value and integrity

How We Work?

Define, Design and Deliver (D3) is our in-house delivery philosophy. It’s culled from agile and rapid methodologies and focused on ‘just enough design’. We embrace this philosophy in everything we do, leading to numerous client success stories and indeed to our own success.

We embrace change, empowering and trusting our people and building long and valuable relationships with our employees, our customers and our partners. We work flexibly, even adopting traditional/waterfall methods where circumstances demand it. At Hoonartek, the focus is always on delivery and value.

Job Description

Roles & Responsibilities

Design, develop, and maintain PySpark-based data processing pipelines
Perform migration and reconfiguration of Spark workloads across different execution environments (e.g., containers to managed platforms like Dataproc)
Execute and validate automated code conversion or migration utilities
Analyze and resolve code compatibility and runtime issues during platform transitions
Perform performance tuning and optimization of Spark jobs for:

Execution efficiency

Resource utilization

Cost effectiveness

Support benchmarking and performance analysis across environments
Troubleshoot failures and ensure stable and reliable job execution
Adhere to best practices for:

Distributed processing

Code modularity and maintainability

Collaborate with cross-functional teams for integration and deployment
Maintain documentation for code changes, configurations, and known issues

Primary Skillsets

Strong expertise in PySpark / Apache Spark
Experience with distributed data processing frameworks
Hands-on with Spark performance tuning and optimization techniques
Proficiency in:

Spark SQL

DataFrames / RDD operations

Understanding of Spark internals:

Execution plans, partitioning, shuffle operations

Experience with GCP services (Dataproc, GCS, BigQuery)
Exposure to containerized environments (Kubernetes / GKE)
Familiarity with automation scripting (Python, Shell)

Secondary Skillsets

Knowledge of cloud cost optimization principles
Experience with logging, monitoring, and debugging tools
Basic understanding of CI/CD pipelines

Job Requirement

Roles & Responsibilities

Design, develop, and maintain PySpark-based data processing pipelines
Perform migration and reconfiguration of Spark workloads across different execution environments (e.g., containers to managed platforms like Dataproc)
Execute and validate automated code conversion or migration utilities
Analyze and resolve code compatibility and runtime issues during platform transitions
Perform performance tuning and optimization of Spark jobs for:

Execution efficiency

Resource utilization

Cost effectiveness

Support benchmarking and performance analysis across environments
Troubleshoot failures and ensure stable and reliable job execution
Adhere to best practices for:

Distributed processing

Code modularity and maintainability

Collaborate with cross-functional teams for integration and deployment
Maintain documentation for code changes, configurations, and known issues

Primary Skillsets

Strong expertise in PySpark / Apache Spark
Experience with distributed data processing frameworks
Hands-on with Spark performance tuning and optimization techniques
Proficiency in:

Spark SQL

DataFrames / RDD operations

Understanding of Spark internals:

Execution plans, partitioning, shuffle operations

Experience with GCP services (Dataproc, GCS, BigQuery)
Exposure to containerized environments (Kubernetes / GKE)
Familiarity with automation scripting (Python, Shell)

Secondary Skillsets

Knowledge of cloud cost optimization principles
Experience with logging, monitoring, and debugging tools
Basic understanding of CI/CD pipelines

Apply Now

Refine Your Search

data engineer – enterprise data platform & analytics jobs in online

PySPark /Spark & Dataproc Senior Engineer

Agentic Product Manager

Senior Vmware Technical Trainer

IT Project Manager

SailPoint IAM Operations Senior Associate L3

AI/ML Expert

Senior Technical Consultant - CISCO Security

Software Engineer | AI Platforms

Presales Solutions Architect - Observability

Staff Software Engineer, QE

Security Dashboard Engineer / Technical Lead

Technical Lead / Engineering Manager, Full Stack - Gen AI (India)

Senior Sales Engineer

Azure Databricks Administrator

Staff DBA - Netwrix DevOps Group

Senior Technical Sales Engineer

TechLead-Fullstack(Node, React)

Principal Backend Engineer

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