198 Cloudera Jobs - Page 2

12+ Years experience in Big data Space across Architecture, Design, Development, testing & Deployment, full understanding in SDLC. 1. Experience of Hadoop and related technology stack experience 2. Experience of the Hadoop Eco-system(HDP+CDP) / Big Data (especially HIVE) Hand on experience with programming languages such as Java/Scala/python Hand-on experience/knowledge on Spark3. Being responsible and focusing on uptime and reliable running of all or ingestion/ETL jobs4. Good SQL and used to work in a Unix/Linux environment is a must.5. Create and maintain optimal data pipeline architecture.6. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.7. Good to have cloud experience8. Good to have experience for Hadoop integration with data visualization tools like PowerBI. Location Mumbai, Pune, Chennai, Hyderabad, Coimbatore, Kolkata

LocationMumbai Experience15+ years in data engineering/architecture Role Overview: Lead the architectural design and implementation of a secure, scalable Cloudera-based Data Lakehouse for one of India’s top public sector banks. Key Responsibilities: * Design end-to-end Lakehouse architecture on Cloudera * Define data ingestion, processing, storage, and consumption layers * Guide data modeling, governance, lineage, and security best practices * Define migration roadmap from existing DWH to CDP * Lead reviews with client stakeholders and engineering teams Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required: * Proven experience with Cloudera CDP, Spark, Hive, HDFS, Iceberg * Deep understanding of Lakehouse patterns and data mesh principles * Familiarity with data governance tools (e.g., Apache Atlas, Collibra) * Banking/FSI domain knowledge highly desirable

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies. Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers.

Role Overview : Seeking an experienced Apache Airflow specialist to design and manage data orchestration pipelines for batch/streaming workflows in a Cloudera environment. Key Responsibilities : Design, schedule, and monitor DAGs for ETL/ELT pipelines Integrate Airflow with Cloudera services and external APIs Implement retries, alerts, logging, and failure recovery Collaborate with data engineers and DevOps teams Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required : Experience 3–8 years Expertise in Airflow 2.x, Python, Bash Knowledge of CI/CD for Airflow DAGs Proven experience with Cloudera CDP, Spark/Hive-based data pipelines Integration with Kafka, REST APIs, databases

Role Overview : Hiring an ML Engineer with experience in Cloudera ML to support end-to-end model development, deployment, and monitoring on the CDP platform. Key Responsibilities : Develop and deploy models using CML workspaces Build CI/CD pipelines for ML lifecycle Integrate with governance and monitoring tools Enable secure model serving via REST APIs Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required : Experience in Cloudera ML, Spark MLlib, or scikit-learn ML pipeline automation (MLflow, Airflow, or equivalent) Model governance, lineage, and versioning API exposure for real-time inference

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

Role Overview : As a Big Data Engineer, you'll design and build robust data pipelines on Cloudera using Spark (Scala/PySpark) for ingestion, transformation, and processing of high-volume data from banking systems. Key Responsibilities : Build scalable batch and real-time ETL pipelines using Spark and Hive Integrate structured and unstructured data sources Perform performance tuning and code optimization Support orchestration and job scheduling (NiFi, Airflow) Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience 3-15 Years Proficiency in PySpark/Scala with Hive/Impala Experience with data partitioning, bucketing, and optimization Familiarity with Kafka, Iceberg, NiFi is a must Knowledge of banking or financial datasets is a plus

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies. Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers AWS S3 , Redshift , and EMR for data storage and distributed processing. AWS Lambda , AWS Step Functions , and AWS Glue to build serverless, event-driven data workflows and orchestrate ETL processes

Role Overview : We are hiring aTalend Data Quality Developerto design and implement robust data quality (DQ) frameworks in a Cloudera-based data lakehouse environment. The role focuses on building rule-driven validation and monitoring processes for migrated data pipelines, ensuring high levels of data trust and regulatory compliance across critical banking domains. Key Responsibilities : Design and implement data quality rules using Talend DQ Studio , tailored to validate customer, account, transaction, and KYC datasets within the Cloudera Lakehouse. Create reusable templates for profiling, validation, standardization, and exception handling. Integrate DQ checks within PySpark-based ingestion and transformation pipelines targeting Apache Iceberg tables . Ensure compatibility with Cloudera components (HDFS, Hive, Iceberg, Ranger, Atlas) and job orchestration frameworks (Airflow/Oozie). Perform initial and ongoing data profiling on source and target systems to detect data anomalies and drive rule definitions. Monitor and report DQ metrics through dashboards and exception reports. Work closely with data governance, architecture, and business teams to align DQ rules with enterprise definitions and regulatory requirements. Support lineage and metadata integration with tools like Apache Atlas or external catalogs. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience 5–10 years in data management, with 3+ years in Talend Data Quality tools. Platforms Experience in Cloudera Data Platform (CDP) , with understanding of Iceberg , Hive , HDFS , and Spark ecosystems. Languages/Tools Talend Studio (DQ module), SQL, Python (preferred), Bash scripting. Data Concepts Strong grasp of data quality dimensions—completeness, consistency, accuracy, timeliness, uniqueness. Banking Exposure Experience with financial services data (CIF, AML, KYC, product masters) is highly preferred.

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

Location Mumbai Role Overview : As a Big Data Engineer, you'll design and build robust data pipelines on Cloudera using Spark (Scala/PySpark) for ingestion, transformation, and processing of high-volume data from banking systems. Key Responsibilities : Build scalable batch and real-time ETL pipelines using Spark and Hive Integrate structured and unstructured data sources Perform performance tuning and code optimization Support orchestration and job scheduling (NiFi, Airflow) Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience3–15 years Proficiency in PySpark/Scala with Hive/Impala Experience with data partitioning, bucketing, and optimization Familiarity with Kafka, Iceberg, NiFi is a must Knowledge of banking or financial datasets is a plus

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

Strong experience in Python Good experience in Databricks Experience working in AWS/Azure Cloud Platform. Experience working with REST APIs and services, messaging and event technologies. Experience with ETL or building Data Pipeline tools Experience with streaming platforms such as Kafka. Demonstrated experience working with large and complex data sets. Ability to document data pipeline architecture and design Experience in Airflow is nice to have To build complex Deltalake

Total Yrs. of Experience 5+ Yrs Relevant Yrs. of experience 3 to 4 Yrs No of Open Positions 8 Mandatory skills Cloudera , Support Experience Other Mandate -Ready to work from client Location (Kharadi) - Flexible to work in India /UK shift hrs Location Kharadi , Pune

Skills: Cloudera, Big Data, Hadoop, SPARK, Kafka, Hive, CDH Clusters: Design and implement Cloudera-based dataplatforms, including cluster sizing, configuration, and optimization. Install, configure, and administer Cloudera Manager and CDP clusters, managingall aspects of the cluster lifecycle. Monitor and troubleshoot platform performance, identifying and resolving issuespromptly. Review the maintain the data ingestion and processing pipelines on the Clouderaplatform. Collaborate with data engineers and datascientists to design and optimize data models, ensuring efficient data storageand retrieval. Implement and enforce security measures for the Cloudera platform, includingauthentication, authorization, and encryption. Manage platform user access and permissions, ensuring compliance with dataprivacy regulations and internal policies. Experience in creating Technology Road Mapsfor Cloudera Platform. Stay up-to-date with the latest Cloudera and big datatechnologies, and recommend and implement relevant updates and enhancements tothe platform. Experience in Planning, testing, andexecuting upgrades involving Cloudera components and ensuring platformstability and security. Document platformconfigurations, processes, and procedures, and provide training and support toother team members as needed. Bachelor's degree in Computer Science, Engineering, or a related field. Proven experience as a Cloudera platform engineer or similar role, with astrong understanding of Cloudera Manager and CDH clusters. Expertise in designing, implementing, and maintaining scalable andhigh-performance data platforms using Cloudera technologies such as Hadoop,Spark, Hive, Kafka. Strong knowledge of big data concepts and technologies, data modeling, and datawarehousing principles. Familiarity with data security and compliance requirements, and experienceimplementing security measures for Cloudera platforms. Proficiency in Linux system administration and scripting languages (e.g.,Shell, Python). Strong troubleshooting and problem-solving skills, with the ability to diagnoseand resolve platform issues quickly. Excellent communication and collaboration skills, with the ability to workeffectively in cross-functional teams. Experience on Azure Data Factory/Azure Databricks/Azure Synapse is a plus

Responsibilities: Implemented Big Data platform on Cloudera Hadoop ecosystem, good knowledge of configuring and optimizing Cloudera. Enhance and maintain data warehouse implementation. Implement analytic solutions and multi-tenant data access patterns. Design and implement scalable, secure Azure infrastructure to host our big data analytics platform. Provide knowledge of network topology, security groups, and connectivity patterns across multiple Azure regions. Required Skills and Experience: Develop and implement data governance strategies using Apache Ranger/DBT/ZooKeeper. Red hat open shift administration. Establish and lead a multi-tiered (L1/L2/L3) technical support team for our big data analytics p latform consisting of infrastructure and application support engineers. Develop comprehensive support processes, procedures, and documentation. Create and maintain standard operating procedures (SOPs) for common issues and resolutions. Design and implement incident management workflows and escalation paths. Qualifications: 7+ years of industry experience with Support/Admin. Cloudera Must have configured, administered and managed cloudera cluster on production. Administration for other big-data tools like Kafka, Nifi, trino, dbt. Experience on Azure. Work Location: Gurgaon (Hybrid). The candidate will have the flexibility to work on client location.

Job Information Job Opening ID ZR_1688_JOB Date Opened 24/12/2022 Industry Technology Job Type Work Experience 12-15 years Job Title Big Data Architect City Mumbai Province Maharashtra Country India Postal Code 400008 Number of Positions 4 LocationMumbai, Pune, Chennai, Hyderabad, Coimbatore, Kolkata 12+ Years experience in Big data Space across Architecture, Design, Development, testing & Deployment, full understanding in SDLC. 1. Experience of Hadoop and related technology stack experience 2. Experience of the Hadoop Eco-system(HDP+CDP) / Big Data (especially HIVE) Hand on experience with programming languages such as Java/Scala/python Hand-on experience/knowledge on Spark3. Being responsible and focusing on uptime and reliable running of all or ingestion/ETL jobs4. Good SQL and used to work in a Unix/Linux environment is a must.5. Create and maintain optimal data pipeline architecture.6. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.7. Good to have cloud experience8. Good to have experience for Hadoop integration with data visualization tools like PowerBI. check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested

Job Information Job Opening ID ZR_2199_JOB Date Opened 15/04/2024 Industry Technology Job Type Work Experience 6-10 years Job Title Sr Data Engineer City Chennai Province Tamil Nadu Country India Postal Code 600004 Number of Positions 4 Strong experience in Python Good experience in Databricks Experience working in AWS/Azure Cloud Platform. Experience working with REST APIs and services, messaging and event technologies. Experience with ETL or building Data Pipeline tools Experience with streaming platforms such as Kafka. Demonstrated experience working with large and complex data sets. Ability to document data pipeline architecture and design Experience in Airflow is nice to have To build complex Deltalake check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#2B39C2;border-color:#2B39C2;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> I'm interested

Job Title: Data Engineer (Spark/Scala/Cloudera) Location: Chennai/Pune Job Type : Full time Experience Level: 6- 9 years Job Summary: We are seeking a skilled and motivated Data Engineer to join our data engineering team. The ideal candidate will have deep experience with Apache Spark, Scala, and Cloudera Hadoop ecosystem. You will be responsible for building scalable data pipelines, optimizing data processing workflows, and ensuring the reliability and performance of our big data platform. Key Responsibilities: Design, build, and maintain scalable and efficient ETL/ELT pipelines using Spark and Scala. Work with large-scale datasets on the Cloudera Data Platform (CDP). Collaborate with data scientists, analysts, and other stakeholders to ensure data availability and quality. Optimize Spark jobs for performance and resource utilization. Implement and maintain data governance, security, and compliance standards. Monitor and troubleshoot data pipeline failures and ensure high data reliability. Participate in code reviews, testing, and deployment activities. Document architecture, processes, and best practices. Required Skills and Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or related field. 6+ years of experience in big data engineering roles. 2 + Years of Hands on experience into Scala Proficient in Apache Spark (Core/DataFrame/SQL/RDD APIs). Strong programming skills in Scala. Hands-on experience with the Cloudera Hadoop ecosystem (e.g., HDFS, Hive, Impala, HBase, Oozie). Familiarity with distributed computing and data partitioning concepts. Strong understanding of data structures, algorithms, and software engineering principles. Experience with CI/CD pipelines and version control systems (e.g., Git). Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus. Preferred Qualifications: Experience with Cloudera Manager and Cloudera Navigator. Exposure to Kafka, NiFi, or Airflow. Familiarity with data lake, data warehouse, and lakehouse architectures. Preferred candidate profile

Role & responsibilities Data Engineer with Spark Scala & Cloudera Sr Data Engineer(Spark/Scala/Cloudera). . Good Exp inn Scala Mandatory 2 YEARS If Interested Kindly share below details: Total Exp: Rel Exp: Current Ctc: Expected Ctc: Notice: If serving Notice pls mention Lwd: Current location: Pref Location: Work from Office 5 Days in a week: Y/N Available to take Teams video call virtual Interview with Laptop on this weekend Saturday, 7th June: Y/N Will confirm time slot Shortly... Preferred candidate profile

Fusion Plus Solutions Inc is looking for Data Engineer to join our dynamic team and embark on a rewarding career journey. Liaising with coworkers and clients to elucidate the requirements for each task. Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed. Reformulating existing frameworks to optimize their functioning. Testing such structures to ensure that they are fit for use. Preparing raw data for manipulation by data scientists. Detecting and correcting errors in your work. Ensuring that your work remains backed up and readily accessible to relevant coworkers. Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.

Tech Stalwart Solution Private Limited is looking for Sr. Data Engineer to join our dynamic team and embark on a rewarding career journey. Liaising with coworkers and clients to elucidate the requirements for each task. Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed. Reformulating existing frameworks to optimize their functioning. Testing such structures to ensure that they are fit for use. Preparing raw data for manipulation by data scientists. Detecting and correcting errors in your work. Ensuring that your work remains backed up and readily accessible to relevant coworkers. Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.

Mega Walkin Drive for Lead Analyst/Senior Software Engineer - Data Engineer Shift Timings : Shift: General Shift (5 Days WFO for initial 8 weeks) Your future duties and responsibilities: Job Overview: CGI is looking for a talented and motivated Data Engineer with strong expertise in Python, Apache Spark, HDFS, and MongoDB to build and manage scalable, efficient, and reliable data pipelines and infrastructure Youll play a key role in transforming raw data into actionable insights, working closely with data scientists, analysts, and business teams. Key Responsibilities: Design, develop, and maintain scalable data pipelines using Python and Spark. Ingest, process, and transform large datasets from various sources into usable formats. Manage and optimize data storage using HDFS and MongoDB. Ensure high availability and performance of data infrastructure. Implement data quality checks, validations, and monitoring processes. Collaborate with cross-functional teams to understand data needs and deliver solutions. Write reusable and maintainable code with strong documentation practices. Optimize performance of data workflows and troubleshoot bottlenecks. Maintain data governance, privacy, and security best practices. Required qualifications to be successful in this role: Minimum 6 years of experience as a Data Engineer or similar role. Strong proficiency in Python for data manipulation and pipeline development. Hands-on experience with Apache Spark for large-scale data processing. Experience with HDFS and distributed data storage systems. Proficient in working with MongoDB, including data modeling, indexing, and querying. Strong understanding of data architecture, data modeling, and performance tuning. Familiarity with version control tools like Git. Experience with workflow orchestration tools (e.g., Airflow, Luigi) is a plus. Knowledge of cloud services (AWS, GCP, or Azure) is preferred. Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Preferred Skills: Experience with containerization (Docker, Kubernetes). Knowledge of real-time data streaming tools like Kafka. Familiarity with data visualization tools (e.g., Power BI, Tableau). Exposure to Agile/Scrum methodologies. Skills: English Oracle Python Java Notice Period- 0-45 Days Pre requisites : Aadhar Card a copy, PAN card copy, UAN Disclaimer : The selected candidates will initially be required to work from the office for 8 weeks before transitioning to a hybrid model with 2 days of work from the office each week.