Roles & Responsibilities: Oracle Warehouse Builder, OWB, Oracle Workflow Builder, Oracle TBSS Oracle Warehouse Builder 9i (Client Version 9.0.2.62.3/Repository Version 9.0.2.0.0) Oracle Warehouse Builder 4 Oracle Workflow Builder 2.6.2 Oracle Database 10gTNS for IBM/AIX RISC System/6000Version 10.2.0.5.0 - Production More than 5 years experience on Oracle Warehouse Builder (OWB) and Oracle Workflow Builder Expert Knowledge on Oracle PL/SQL to develop individual code objects to entire DataMarts. Scheduling tools Oracle TBSS (DBMS_SCHEDULER jobs to create and run) and trigger based for file sources based on control files. Must have design and development experience in data pipeline solutions from different source systems (FILES, Oracle) to data lakes. Must have involved in creating/designing Hive tables and loading analyzing data using hive queries. Must have knowledge in CA Workload Automation DE 12.2 to create jobs and scheduling. Extensive knowledge on entire life cycle of Change/Incident/Problem management by using ServiceNow. Oracle Warehouse Builder 9i (Client Version 9.0.2.62.3/Repository Version 9.0.2.0.0). Oracle Warehouse Builder 4 Oracle Workflow Builder 2.6.2 Oracle Database 10gTNS for IBM/AIX RISC System/6000Version 10.2.0.5.0 - Production. Oracle Enterprise Manager 10gR1.(Monitoring jobs and tablespaces utilization) Extensive knowledge in fetching Mainframe Cobol files(ASCII AND EBSDIC formats) to the landing area and processing(formatting) and loading(Error handling) of these files to oracle tables by using SQL*Loader and External tables. Extensive knowledge in Oracle Forms 6 to integrate with OWB 4. Extensive knowledge on entire life cycle of Change/Incident/Problem management by using Service-Now. work closely with the Business owner teams and Functional/Data analysts in the entire development/BAU process. Work closely with AIX support, DBA support teams for access privileges and storage issues etc. work closely with the Batch Operations team and MFT teams for file transfer issues. Migration of Oracle to Hadoop eco system: Must have working experience in Hadoop eco system elements like HDFS,MapReduce,YARN etc. Must have working knowledge on Scala & Spark Dataframes to convert the existing code to Hadoop data lakes. Must have design and development experience in data pipeline solutions from different source systems (FILES, Oracle) to data lakes. Must have involved in creating/designing Hive tables and loading analyzing data using hive queries. Must have knowledge in creating Hive partitions, Dynamic partitions and buckets. Must have knowledge in CA Workload Automation DE 12.2 to create jobs and scheduling. Use Denodo for Data virtualization to the required data access for end users.

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : PySpark Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will engage in the design, construction, and configuration of applications tailored to fulfill specific business processes and application requirements. Your typical day will involve collaborating with team members to understand project needs, developing innovative solutions, and ensuring that applications are optimized for performance and usability. You will also participate in testing and debugging processes to ensure the applications function as intended, while continuously seeking ways to enhance application efficiency and user experience. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Assist in the documentation of application specifications and user guides.- Engage in code reviews to ensure adherence to best practices and standards. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Strong understanding of data integration and ETL processes.- Experience with cloud computing platforms and services.- Familiarity with programming languages such as Python or Scala.- Knowledge of data visualization techniques and tools. Additional Information:- The candidate should have minimum 2 years of experience in Databricks Unified Data Analytics Platform.- This position is based at our Chennai office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : Apache Spark Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Developer, you will be responsible for designing, building, and configuring applications to meet business process and application requirements. You will play a crucial role in developing solutions that align with organizational goals and enhance operational efficiency. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Collaborate with cross-functional teams to analyze business requirements and translate them into technical solutions.- Develop and implement software solutions using Apache Spark to enhance application functionality.- Troubleshoot and debug applications to optimize performance and ensure seamless operation.- Stay updated with industry trends and best practices to continuously improve application development processes.- Provide technical guidance and support to junior team members to foster skill development. Professional & Technical Skills: - Must To Have Skills: Proficiency in Apache Spark.- Strong understanding of big data processing and distributed computing.- Experience with data processing frameworks like Hadoop and Spark SQL.- Hands-on experience in developing scalable and efficient applications using Apache Spark.- Knowledge of programming languages such as Scala or Python. Additional Information:- The candidate should have a minimum of 2 years of experience in Apache Spark.- This position is based at our Pune office.- A 15 years full-time education is required. Qualification 15 years full time education

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : PySpark Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Lead, you will lead the effort to design, build, and configure applications, acting as the primary point of contact. Your typical day will involve collaborating with various teams to ensure that application development aligns with business objectives, overseeing project timelines, and facilitating communication among stakeholders to drive project success. You will also engage in problem-solving activities, providing guidance and support to your team while ensuring that best practices are followed throughout the development process. Your role will be pivotal in shaping the direction of application projects and ensuring that they meet the needs of the organization and its clients. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Facilitate training and development opportunities for team members to enhance their skills.- Monitor project progress and implement necessary adjustments to ensure timely delivery. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Good To Have Skills: Experience with cloud computing platforms such as AWS or Azure.- Strong understanding of data engineering principles and practices.- Experience in application development using modern programming languages.- Familiarity with Agile methodologies and project management tools. Additional Information:- The candidate should have minimum 5 years of experience in Databricks Unified Data Analytics Platform.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Roles and Responsibilities: Experience in GLUE AWS Experience with one or more of the followingSpark, Scala, Python, and/or R . Experience in API development with NodeJS Experience with AWS (S3, EC2) or other cloud provider Experience in Data Virtualization tools like Dremio and Athena is a plus Should be technically proficient in Big Data concepts Should be technically proficient in Hadoop and noSQL (MongoDB) Good communication and documentation skills

Roles & Responsibilities: Total 8-10 years of working experience Experience/Needs 8-10 Years of experience with big data tools like Spark, Kafka, Hadoop etc. Design and deliver consumer-centric high performant systems. You would be dealing with huge volumes of data sets arriving through batch and streaming platforms. You will be responsible to build and deliver data pipelines that process, transform, integrate and enrich data to meet various demands from business Mentor team on infrastructural, networking, data migration, monitoring and troubleshooting aspects Focus on automation using Infrastructure as a Code (IaaC), Jenkins, devOps etc. Design, build, test and deploy streaming pipelines for data processing in real time and at scale Experience with stream-processing systems like Storm, Spark-Streaming, Flink etc.. Experience with object-oriented/object function scripting languagesScala, Java, etc. Develop software systems using test driven development employing CI/CD practices Partner with other engineers and team members to develop software that meets business needs Follow Agile methodology for software development and technical documentation Good to have banking/finance domain knowledge Strong written and oral communication, presentation and interpersonal skills. Exceptional analytical, conceptual, and problem-solving abilities Able to prioritize and execute tasks in a high-pressure environment Experience working in a team-oriented, collaborative environment 8-10 years of hand on coding experience Proficient in Java, with a good knowledge of its ecosystems Experience with writing Spark code using scala language Experience with BigData tools like Sqoop, Hive, Pig, Hue Solid understanding of object-oriented programming and HDFS concepts Familiar with various design and architectural patterns Experience with big data toolsHadoop, Spark, Kafka, fink, Hive, Sqoop etc. Experience with relational SQL and NoSQL databases like MySQL, PostgreSQL, Mongo dB and Cassandra Experience with data pipeline tools like Airflow, etc. Experience with AWS cloud servicesEC2, S3, EMR, RDS, Redshift, BigQuery Experience with stream-processing systemsStorm, Spark-Streaming, Flink etc. Experience with object-oriented/object function scripting languagesPython, Java, Scala, etc. Expertise in design / developing platform components like caching, messaging, event processing, automation, transformation and tooling frameworks Location:Pune/ Mumbai/ Bangalore/ Chennai

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

Engineer the data transformations and analysis for the Cash Equities Trading platform. Technology SME on the real-time stream processing paradigm. Bring your experience in Low latency, High through-put, auto scaling platform design and implementation. Implementing an end-to-end platform service, assessing the operations and non-functional needs clearly. Drive and document technical and functional decisions with appropriate diligence. Provide operational support and manage incidents. Requirements To be successful in this role, you should meet the following requirements: 10+ years of experience in data engineering technology and tools. Preferred having experience with Java / Scala based implementations for enterprise-wide platforms. Experience with Apache Beam, Google Dataflow, Apache Kafka for real-time steam processing technology stack. Complex state-full processing of events with partitioning for higher throughputs. Have dealt with fine-tuning the through-puts and improving the performance aspects on data pipelines. Experience with analytical data store optimizations, querying and managing them. Experience with alternate data engineering tools (Apache Flink, Apache Spark etc) Automated CI/CD or operations concerns on the engineering platforms. Interpreting problems from functional context and transforming them into technology solutions.

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 Azure 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 and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform 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 / Azure 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 6 - 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 Azure; Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Good to excellent SQL skills Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers

Were looking for an experienced Senior Data Engineer to lead the design and development of scalable data solutions at our company. The ideal candidate will have extensive hands-on experience in data warehousing, ETL/ELT architecture, and cloud platforms like AWS, Azure, or GCP. You will work closely with both technical and business teams, mentoring engineers while driving data quality, security, and performance optimization. Responsibilities: Lead the design of data warehouses, lakes, and ETL workflows. Collaborate with teams to gather requirements and build scalable solutions. Ensure data governance, security, and optimal performance of systems. Mentor junior engineers and drive end-to-end project delivery.: 6+ years of experience in data engineering, including at least 2 full-cycle datawarehouse projects. Strong skills in SQL, ETL tools (e.g., Pentaho, dbt), and cloud platforms. Expertise in big data tools (e.g., Apache Spark, Kafka). Excellent communication skills and leadership abilities.PreferredExperience with workflow orchestration tools (e.g., Airflow), real-time data,and DataOps practices.

As a BigData Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: 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 Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Big Data Developer, Hadoop, Hive, Spark, PySpark, Strong SQL. Ability to incorporate a variety of statistical and machine learning techniques. Basic understanding of Cloud (AWS,Azure, etc). Ability to use programming languages like Java, Python, Scala, etc., to build pipelines to extract and transform data from a repository to a data consumer Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed. Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop and Java Preferred technical and professional experience Basic understanding or experience with predictive/prescriptive modeling skills You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions

About Company Job Description Key responsibilities: 1. Understand, implement, and automate ETL pipelines with better industry standards 2. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, design infrastructure for greater scalability, etc 3. Developing, integrating, testing, and maintaining existing and new applications 4. Design, and create data pipelines (data lake / data warehouses) for real world energy analytical solutions 5. Expert-level proficiency in Python (preferred) for automating everyday tasks 6. Strong understanding and experience in distributed computing frameworks, particularly Spark, Spark-SQL, Kafka, Spark Streaming, Hive, Azure Databricks etc 7. Limited experience in using other leading cloud platforms preferably Azure. 8. Hands on experience on Azure data factory, logic app, Analysis service, Azure blob storage etc. 9. Ability to work in a team in an agile setting, familiarity with JIRA and clear understanding of how Git works 10. Must have 5-7 years of experience

As an Application Developer, you will lead IBM into the future by translating system requirements into the design and development of customized systems in an agile environment. The success of IBM is in your hands as you transform vital business needs into code and drive innovation. Your work will power IBM and its clients globally, collaborating and integrating code into enterprise systems. You will have access to the latest education, tools and technology, and a limitless career path with the world’s technology leader. Come to IBM and make a global impact Responsibilities: Responsible to manage end to end feature development and resolve challenges faced in implementing the same Learn new technologies and implement the same in feature development within the time frame provided Manage debugging, finding root cause analysis and fixing the issues reported on Content Management back end software system fixing the issues reported on Content Management back end software system Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Overall, more than 6 years of experience with more than 4+ years of Strong Hands on experience in Python and Spark Strong technical abilities to understand, design, write and debug to develop applications on Python and Pyspark. Good to Have;- Hands on Experience on cloud technology AWS/GCP/Azure strong problem-solving skill Preferred technical and professional experience Good to Have;- Hands on Experience on cloud technology AWS/GCP/Azure

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 Azure 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 and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform 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 / Azure 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 Azure Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Exposure to streaming solutions and message brokers like Kafka technologies Experience Unix / Linux Commands and basic work experience in Shell Scripting Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers

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

Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. 7+ Yrs total experience in Data Engineering projects & 4+ years of relevant experience on Azure technology services and Python Azure Azure data factory, ADLS- Azure data lake store, Azure data bricks, Mandatory Programming languages Py-Spark, PL/SQL, Spark SQL Database SQL DB Experience with AzureADLS, Databricks, Stream Analytics, SQL DW, COSMOS DB, Analysis Services, Azure Functions, Serverless Architecture, ARM Templates Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with object-oriented/object function scripting languagesPython, SQL, Scala, Spark-SQL etc. Data Warehousing experience with strong domain Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Intuitive individual with an ability to manage change and proven time management Proven interpersonal skills while contributing to team effort by accomplishing related results as needed Up-to-date technical knowledge by attending educational workshops, reviewing publications Preferred technical and professional experience Experience with AzureADLS, Databricks, Stream Analytics, SQL DW, COSMOS DB, Analysis Services, Azure Functions, Serverless Architecture, ARM Templates Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with object-oriented/object function scripting languagesPython, SQL, Scala, Spark-SQL etc.

Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modeling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total Exp-6-7 Yrs (Relevant-4-5 Yrs) Mandatory Skills: Azure Databricks, Python/PySpark, SQL, Github, - Azure Devops - Azure Blob Ability to use programming languages like Java, Python, Scala, etc., to build pipelines to extract and transform data from a repository to a data consumer Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed. Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop and Java Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

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 an Associate Software Developer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise seach applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modeling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total Exp-6-7 Yrs (Relevant-4-5 Yrs) Mandatory Skills: Azure Databricks, Python/PySpark, SQL, Github, - Azure Devops - Azure Blob Ability to use programming languages like Java, Python, Scala, etc., to build pipelines to extract and transform data from a repository to a data consumer Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed. Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop and Java Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

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

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