Software Engineer - (Sr. Spark)

Jobgether; India; On-site; INR 2,500,000 - 4,200,000; Full time

Benefits offered by this job

Full-time

Ahmedabad on-site

Hyderabad on-site

Vijayawada on-site

Job summary

Jobgether, on behalf of a partner company in India, seeks a Senior Spark Software Engineer. You will design and optimize scalable data solutions, owning the end-to-end data engineering lifecycle from design to operations, using Spark, Spark SQL, and cloud-native services.

You’ll mentor engineers and collaborate with clients to translate business needs into robust technical implementations. You'll contribute to multi-cloud data platforms, data lakes, ETL pipelines, and data warehouses, delivering

Qualifications

• Strong OO design and software development experience.
• Experience designing, building, testing, deploying, and operating end-to-end data processing systems.
• Hands-on expertise with Apache Spark, Spark SQL, and associated big data technologies.
• Experience building enterprise data platforms covering data ingestion, data lakes, ETL pipelines, and data warehousing.
• Strong coding, debugging, troubleshooting, and performance optimization skills.
• Experience deploying and operating production-grade data engineering solutions using cloud-native services.

Responsibilities

• Design, develop, test, deploy, and operate end-to-end data processing systems.
• Build and optimize big data solutions using Apache Spark, Spark SQL, and related technologies across databases, streaming platforms, and data warehouses.
• Apply object-oriented design principles and sound software engineering practices to develop maintainable, efficient, and scalable applications.
• Build and maintain enterprise data platforms, including data ingestion pipelines, data lakes, ETL processes, and data warehouses.
• Design and implement efficient production deployments for data engineering projects using cloud-native services and best practices.
• Identify opportunities to improve data processing performance, system reliability, operational efficiency, and deployment workflows.
• Track project progress using lean, efficient processes, proactively identify delivery blockers, and collaborate with team members to resolve issues.
• Lead and mentor engineering teams, provide technical guidance, and promote high standards of coding, debugging, testing, and delivery.
• Work closely with clients and stakeholders to understand business requirements, communicate technical solutions clearly, and ensure successful project outcomes.
• Contribute to multi-cloud data engineering initiatives and help deliver solutions tailored to different cloud environments and business domains.

Skills

Apache Spark

Spark SQL

Big Data

Data Pipelines

Cloud-Native

Leadership

Mentoring

Software Design

OO Design

Communication Skills

Tools

Hadoop

HDFS

Hive

Impala

HBase

MongoDB

Cassandra

Kafka

Multi-Cloud Deployments

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Software Engineer – (Sr. Spark) based in India.

As a Senior Spark Software Engineer, you will design, develop, and optimize scalable big data processing solutions that support complex enterprise needs. You will take ownership of the full data engineering lifecycle, from solution design and development to testing, deployment, and ongoing operations. Working with modern big data technologies and cloud-native services, you will help build robust data platforms that enable efficient data ingestion, transformation, storage, and analysis. You will collaborate with cross-functional and client-facing teams to translate business requirements into reliable technical solutions. In this role, you will also guide team members, mentor engineers, and promote effective development practices. This is an opportunity to combine deep technical expertise with leadership and deliver high-impact data solutions across multiple industries.

Accountabilities

• Design, develop, test, deploy, and operate end-to-end data processing systems that meet enterprise performance, scalability, and reliability requirements.
• Build and optimize big data solutions using Apache Spark, Spark SQL, and related technologies across databases, streaming platforms, and data warehouses.
• Apply object-oriented design principles and sound software engineering practices to develop maintainable, efficient, and scalable applications.
• Build and maintain enterprise data platforms, including data ingestion pipelines, data lakes, ETL processes, and data warehouses.
• Design and implement efficient production deployments for data engineering projects using cloud-native services and best practices.
• Identify opportunities to improve data processing performance, system reliability, operational efficiency, and deployment workflows.
• Track project progress using lean, efficient processes, proactively identify delivery blockers, and collaborate with team members to resolve issues.
• Lead and mentor engineering teams, provide technical guidance, and promote high standards of coding, debugging, testing, and delivery.
• Work closely with clients and stakeholders to understand business requirements, communicate technical solutions clearly, and ensure successful project outcomes.
• Contribute to multi-cloud data engineering initiatives and help deliver solutions tailored to different cloud environments and business domains.

Requirements

• Strong experience in object-oriented design, software development, and implementation.
• Demonstrated experience designing, building, testing, deploying, and operating end-to-end data processing systems.
• Hands-on expertise with Apache Spark, Spark SQL, and associated big data technologies.
• Experience building enterprise data platforms covering data ingestion, data lakes, ETL pipelines, and data warehousing.
• Strong coding, debugging, troubleshooting, and performance optimization skills.
• Experience deploying and operating production-grade data engineering solutions using cloud-native services.
• Familiarity with multi-cloud deployments is an advantage.
• Experience leading technical teams, mentoring engineers, and coordinating delivery across project teams.
• Strong organizational skills, with the ability to track project progress, prioritize deliverables, identify risks, and resolve blockers proactively.
• Excellent communication and presentation skills, including the ability to explain technical concepts and engage effectively with clients.
• Knowledge of additional big data technologies such as Hadoop, HDFS, Hive, Impala, HBase, MongoDB, Cassandra, and Kafka is a plus.
• Domain knowledge in industries such as healthcare, banking and financial services (BFSI), or retail is an advantage.
• A collaborative, delivery-focused mindset, with the ability to balance technical excellence, team leadership, and business objectives.

Benefits

• Full-time opportunity: Join a dedicated engineering team working on enterprise-scale data engineering projects.
• Multiple location options: Opportunities based in Ahmedabad, Hyderabad, or Vijayawada, India.
• Technical growth: Work with Apache Spark, Spark SQL, enterprise data platforms, and modern cloud technologies.
• Leadership opportunities: Apply your technical expertise while mentoring team members and contributing to engineering best practices.
• Enterprise-scale impact: Build and optimize data solutions that support complex business needs across multiple industries.
• Cloud and big data exposure: Gain experience working with cloud-native deployments, distributed data processing, and modern data engineering ecosystems.
• Cross-functional collaboration: Partner with technical teams and clients to solve challenging data problems and deliver measurable outcomes.