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Recently Added Spark Developers in our Network

Akhil Prasad

Akhil PrasadProfile Badge IC

Senior Data Engineer7 Years of Exp
  • Data Warehousing
  • Big Data Technology
  • PySpark
  • Snowflake
  • AWS
  • View all (9)

Skilled in practices around Data Warehousing, Data Marts, Data Models, ETL & ELT for large-scale data management.Built batch & streaming pipelines using Spark & Hadoop ecosystem capable of handling terabytes of data on day-to-day basis.Worked on Cloud migration of thousands of pipelines (On-Primm to GCP).Part of the Data Management team, involved in Automation & Support, Platform Engineering, and Data Governance activities.Build & managed Data Pipeline frameworks (using Python, Scala) used for data ingestion activities across teams/markets.Expert in writing Optimized SQL queries for OLTP & OLAP workloads using Indexes, Join, Aggregate, Window functions, CTEs, and more.Worked in Retail, Banking, Financial Services & Insurance domain.Collaborated on quarterly roadmaps, optimizing resource allocation and ensuring clear stakeholder communication.Led sprint planning, prioritizing backlog, managing team capacity, and providing technical guidance for timely & high-quality delivery.

Ambuj Kumar

Ambuj KumarProfile Badge IC

Senior Data Engineer9 Years of Exp
  • Data Lakes
  • Databases
  • DevOps
  • frameworks
  • Ml frameworks
  • View all (7)

Senior Data Engineer with 9+ years of experience in building data intensive applications, tackling challenging architectural and scalability problems, managing data repos for efficient visualization, for a wide range of products. Highly analytical team player, with the aptitude for prioritization of needs/risks. Constantly striving to streamlining processes and experimenting with optimising and benchmarking solutions. Creative troubleshooter/problem-solver and loves challenges. Experience in implementing ML Algorithms & CI/CD using distributed paradigms of Spark/Flink, in production, on Azure Databricks/AWS Sagemaker/MLFlow. Experience in shaping and implementing Big Data architecture for Medical Devices,Retail, Banking, Games and Transport Logistics domain (IOT).

Aswathy Raj

Aswathy RajProfile Badge IC

Senior Data Engineer12.00 Years of Exp
  • Azure Data Factory
  • Azure DevOps
  • ETL processes
  • Data Modeling
  • View all (7)

Diligent engineer with 12+ years of experience which includes contributions in data science and engineering,development of software framework, platforms, applications and customer interaction with multilingual andmulticultural clients. An effective team player and well versed in various platforms, programming languagesand programming with different databases. Also have extensive experience in all phases of softwaredevelopment, and on waterfall and agile methods of project life cycle.

KUSH SHARMA

KUSH SHARMAProfile Badge IC

Senior Member Technical Staff8.11 Years of Exp
  • Java
  • Python
  • MySQL
  • Agile Scrum
  • Cloud Foundry
  • Grafana
  • Kibana
  • View all (10)

Motivated and Passionate software engineer with 8+ years of experience in developing highly scalable and secured software systems using a variety of technologies like Java, Spring Boot, Python, Microservies, Jenkins, Rest API, GraphQL API, PostgreSql etc. Certified Disciplined Agile Scrum master and a Security champion.

NANDESH REDDY

NANDESH REDDYProfile Badge IC

Big Data Engineer5.2 Years of Exp
  • Python
  • Big Data Technology
  • PySpark
  • Snowflake
  • AWS
  • 組込みLinux
  • NO SQL
  • View all (9)

Experienced data engineer adept at designing and implementing scalable data solutions. Proficient in crafting efficient data pipelines and optimizing data processing workflows. Skilled in diverse big data tech stack, including technologies such as PySpark, Hive, Sqoop, MySQL, HDFS, Hadoop, and possessing fundamental knowledge of Azure services. Self- motivated and ready to learn new technologies, committed to driving data-driven decision- making by ensuring the availability, accuracy, and usability of data.

Nivin Srinivas S

Nivin Srinivas SProfile Badge IC

Senior Data Engineer6 Years of Exp
  • Python
  • SQL
  • Spark
  • Data Warehousing
  • Airflow
  • BigQuery
  • ETL processes
  • View all (10)

Senior Data Engineer with over four years of experience in building scalable data platforms and pipelines and maintaining optimal data infrastructure. Interested to solve challenging problems in a data-driven company.

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Works in 5+ Time Zones

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Top Clients Reviews

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Uplers earned our trust by listening to our problems and finding the perfect talent for our organization.

Barış Ağaçdan
Director
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Uplers helped to source and bring out the top talent in India, any kind of high-level role requirement in terms of skills is always sourced based on the job description we share. The profiles of highly vetted experts were received within a couple of days. It has been credible in terms of scaling our team out of India.

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Uplers efficient, quick process and targeted approach helped us find the right talents quickly. The professionals they provided were not only skilled but also a great fit for our team.

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Uplers' talents consistently deliver high-quality work along with unmatched reliability, work ethic, and dedication to the job.

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Case Studies of Tech Companies

Transform Your Data Strategies with Skilled Apache Spark Developers

Every modern business wants to explore data for insights, make analytical decisions, and compete successfully within available markets. Data volumes are growing exponentially; thus, efficient data strategies have become imperative for survival and success.

Frequently Asked Questions

Uplers provide AI-vetted talent, ensuring a seamless hiring experience. Our efficient process ensures profile shortlisting within 48 hours, allowing you to swiftly onboard qualified professionals within just 2 weeks. Additionally, we prioritize client satisfaction with our flexible terms, including a 30-day cancellation policy and a lifetime free replacement.

You can get the top 3.5% of AI-vetted profiles in less than 48 hours through Uplers. Once you finalize one of the most suitable Spark Developers, Uplers takes care of the entire hiring and onboarding formalities. This typically takes 2-4 weeks depending on your requirements and decision-making time.

The modes of communication through which you can get in touch with a hired Spark Developer include:

  • Email
  • Phone
  • Messaging apps such as WhatsApp, Slack, or Microsoft Teams

Uplers offers a 30-day cancellation policy at no extra cost and lifetime free replacement.

The average cost of hiring a Spark Developer from Uplers starts at $2500. The number varies depending on the experience level of the developer as well as your requirements.

View Our Pricing For 2024 - 25

At Uplers, our screening process ensures a thorough evaluation of candidates' language proficiency, facilitated by our AI-vetting technology. Beyond linguistic skills, we prioritize cultural fitness to ensure seamless integration within your team, fostering a harmonious work environment and seamless collaboration.

Yes, Spark developers are in high demand as big data processing and real-time analytics continue to grow. Apache Spark's scalability, speed, and support for AI/ML make it essential for industries like finance, healthcare, and e-commerce handling large-scale data workloads.

Spark developers are focusing on real-time analytics, AI/ML integration, and cloud-native deployments. Trends include using Spark with Kubernetes, leveraging Delta Lake for better data management, optimizing performance with Spark 3, and integrating with deep learning frameworks for advanced data processing.

Uplers optimizes costs by:

  • Providing offshore talent at 40-50% lower costs than local hiring
  • Offering flexible payment models (hourly, fixed-price, retainer-based)
  • Reducing hiring overhead with full-time remote experts

This maximizes ROI while maintaining high-quality hiring standards.

Yes, Uplers offers:

  • Short-term contract hiring with the option to convert to full-time
  • Performance evaluations before final hiring
  • Low-risk transition periods for new hires

This helps SaaS companies test talent before full commitment.

  • Matches candidates who can work in preferred time zones
  • Provides talent with experience in global remote work environments
  • Ensures cultural & communication fit for distributed teams

This helps SaaS companies build efficient global teams.

AI optimizes hiring by:

  • Auto-generating technical interview questions
  • Assessing candidates' soft skills and cultural fit
  • Detecting hiring biases to ensure fair selection

This results in faster, data-driven hiring decisions.