... and contribute to strategic decisions on platform evolution, including generative AI integration and event-driven systems. Data Science and Machine Learning - Data Science and Machine Learning - Python Database - Database Programming - SQL Big Data - Big Data - Pyspark Data & AI - Data Engineering - Data Quality & Validation ...
... understanding of microservices architecture and distributed systems.- Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines.- Experience with big data technologies like Snowflake.- Strong problem-solving and performance optimization skills.- Exposure to modern DevOps practices, ...
... frameworks for building scalable data pipelines. Understanding of Big Data architectures, data storage, and data processing concepts. Familiarity with cloud-native data storage solutions such as S3, Blob Storage, BigQuery, or Redshift. Experience with data orchestration tools like Apache Airflow or similar. Knowledge of data ...
... Analyze sales pipeline, opportunity, account, pursuit, and performance data to identify trends, exceptions, and reporting gaps. Support automation of recurring data preparation, reporting, validation, and distribution activities using approved tools. Validate data, calculations, filters, refreshes, and reporting outputs to ...
... based on audience needs Proficient in usage of any instructional design tools such as Articulate, Canva, SCORM Strong analytical skills to interpret operational data and identify training areas for improvement What are we looking for Primary skill - Training Needs Analysis (TNA) - P5 Secondary skill - Instructor-Led Training ...
... Certified Professional or similar certifications. Machine Learning: Knowledge of machine learning concepts and experience with popular ML libraries. Knowledge of big data processing (e.g., Spark, Hadoop, Hive, Kafka) Data Orchestration: Apache Airflow. Knowledge of CI/CD pipelines and DevOps practices in a cloud environment. ...
... data from a data source . Data processing: to process, transform and distribute the data to the target location . Data exposition : to distribute and expose the data hosted in the data platform . Data cleaning: to purge the data on the Lake in a secure way . Data tools: data formatter, data anonymizer As a big data engineer, ...
... Experience in card payments and/or retail banking domain. - Hands-on experience across the data analytics lifecycle: programming and querying (Python, SQL, Pyspark), big data platforms (Hadoop, Hive), and business intelligence/visualization (Tableau). - Proven ability to translate complex data into compelling narratives and impactful ...
... containers as well as GCP suite, terraform kubernetes, cloud functions You understand standard ETL patterns, modern data warehousing ideas such as data mesh or data vaulting, and data quality practices regarding test driven design and data observability. You are passionate about all things data: Big data, small data, moving ...
... anomalies. Required Qualifications • 5+ years in QA or software testing, including focused on data pipelines/data warehouses • Proficient in complex SQL and writing data validation queries. • Strong experience with GCP data tools: dbt, BigQuery, Dataflow, Dataproc, Cloud Run, Spanner, AlloyDB, Cloud SQL. • Hands-on with data-quality ...
... workflows to streamline processes and improve efficiency.- Create custom applications using Power Apps to meet business needs.- Write and optimize SQL queries for data extraction and transformation.- Ensure data integrity and reliability across all reporting and dashboard solutions.- Troubleshoot and resolve issues related to ...
... workflows Strong analytical problem solving and debugging skills Additional Responsibilities: Experience with cloud platforms AWS Azure or GCP Familiarity with big data technologies Spark Hadoop Exposure to workflow schedulers Airflow Prefect Cron Knowledge of CI CD pipelines and version control Git Understanding of data governance ...
... containers as well as GCP suite, terraform kubernetes, cloud functions You understand standard ETL patterns, modern data warehousing ideas such as data mesh or data vaulting, and data quality practices regarding test driven design and data observability. You are passionate about all things data: Big data, small data, moving ...
... scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications. Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools. Design, ...
... preparing reports, managing files, storing data, and keeping records organized and updated for easy retrieval and understanding. - 3+ years of overall experience in data engineering or related fields. - 2+ years of experience building data pipelines for structured and unstructured data. - 1+ years of experience with big data technologies ...
... Stakeholder Collaboration & Timezone Alignment: Work during US East Coast hours (EST) to engage with clients, review reports early in the day, and translate ambiguous requirements into scalable analytical solutions.- Advanced Calculations & Data Modeling: Build efficient star/snowflake schemas and develop complex DAX calculations, ...
... Perform data transformation and cleansing using Power Query.- Optimize Power BI reports, dashboards, queries, and data models for improved performance.- Apply data visualization best practices to present complex payment and financial data effectively.- Integrate Power BI with data sources such as SQL Server, Oracle, Snowflake, ...
... design and code a variety of applications covering transaction processing, analytics, user interfaces, and APIs using a blend of cutting-edge technologies across big data, distributed systems, machine learning, and more. As a Software Engineer, you will deliver these products and solutions with speed and agility as part of ...
... efficient scripts using PySpark for large-scale data processing. Familiarity with CI/CD for data pipelines and DevOps practices. Strong problem-solving skills and ability to work in an agile environment. Knowledge of data governance, security, and compliance in Azure. Exposure to big data frameworks and streaming technologies.
Company : Very big MNCRole : GCP Data EngineerExperience : 8 - 15 yrsNotice Period : 30 daysLocation : PAN INDIATech Stack :- GCP data engineer- Pyspark- Dataflow- Dataproc- BigQuery- AirflowKey Responsibilities :- Design, develop, and optimize endtoend data pipelines using PySpark, Dataflow, and Dataproc- Implement data ingestion, ...