Software Engineer - (Sr. Spark)

Jobgether; United States; Remote; USD 19,000 - 25,000; Full time

Benefits offered by this job

Leadership opportunities

Enterprise-scale projects

Multi-cloud exposure

Career development

Job summary

Jobgether is seeking a senior data engineering lead to design, build, test, deploy, and operate end-to-end data processing systems for enterprise-scale needs. You will architect and optimize Spark-based pipelines, data lakes, ETL processes, and data warehouses, ensuring scalability, reliability, and performance across environments.

You will mentor teams, coordinate delivery across project streams, and communicate complex technical concepts to clients.

Qualifications

• Strong experience in object-oriented design, software development, and implementation.
• 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 deploying production-grade data engineering solutions using cloud-native services.
• Familiarity with multi-cloud deployments is an advantage.
• Excellent communication and presentation skills.

Responsibilities

• Design, develop, test, deploy, and operate end-to-end data processing systems.
• Build and optimize big data solutions using Spark, Spark SQL, and related technologies.
• Apply OO design principles to develop maintainable, scalable applications.
• Build and maintain data platforms: ingestion pipelines, data lakes, ETL, and warehousing.
• Design and implement production deployments for data projects using cloud-native services.
• Identify opportunities to improve data processing performance and reliability.
• Track progress and resolve blockers, collaborating with team members.
• Mentor engineering teams and promote coding and testing standards.
• Collaborate with clients and stakeholders to meet business requirements.

Skills

OO Design

Spark & Spark SQL

Data pipelines

Cloud deployments

Tools

Apache Spark

Spark SQL

Hadoop

Kafka

Hive

Job description

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.