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Data Engineer - Python/Spark
Data Engineer - Python/SparkVarite • Hyderabad
Data Engineer - Python / Spark

Data Engineer - Python / Spark

Varite • Hyderabad
30+ days ago
Job description

About The Job :

  • Develops technical tools and programming to cleanse, organize and transform data and to maintain, protect and update data structures and integrity on an automated basis.
  • Applies data extraction, transformation, and loading techniques in order to tie together large data sets from a variety of sources.
  • Partners with both internal & external sources to design, build and oversee the deployment and operation of technology architecture, solutions and software.
  • Designs, develops and programs methods, processes and systems to capture, manage, store and utilize structured and unstructured data to generate actionable insights and solutions.
  • Responsible for the maintenance, improvement, cleaning, and manipulation of data in the business client's operational and analytics databases.
  • Proactively analyzes and evaluates the business client's databases in order to identify and recommend improvements and optimization.

Essential Job Functions :

  • Uses knowledge of existing and emerging data science engineering principles, theories, and techniques to inform business decisions; and produce accurate business insights.
  • Completes projects and assignments of moderate scope and complexity under normal supervision to ensure customer and business needs are met.
  • Applies discretion and independent judgement to interpret data trends and summarize data insights.
  • Assists in the preliminary data exploration, data preparation for accurate model development.
  • Establishes working relationships with others outside area of Data Science Engineering expertise.
  • Prepares presentations of project outputs for external customers with assistance.
  • Design, develop, and maintain scalable data pipelines and systems for data processing.
  • Utilize Data Lakehouse, Spark on Kubernetes and related technologies to manage large-scale data processing.
  • Perform data ingestion from various sources like API's, RDBMS, NoSQL DB's, Kafka, Middleware & Files using Spark and process data into Lakehouse platform.
  • Develop and maintain py-spark scripts for automation of data processing tasks.
  • Implement full and incremental data loading strategies to ensure data consistency and availability.
  • Orchestrate and monitor workflows using Apache Airflow.
  • Ensure code quality and version control using GIT.
  • Troubleshoot and resolve data-related issues in a timely manner.
  • Stay up-to-date with the latest industry trends and technologies to continuously improve our data infrastructure.
  • Design, develop, and maintain scalable data pipelines and systems for data processing.
  • Utilize Data Lakehouse, Spark on Kubernetes and related technologies to manage large-scale data processing.
  • Perform data ingestion from various sources like API's, RDBMS, NoSQL DB's, Kafka, Middleware &
  • Files using Spark and process data into Lakehouse platform.
  • Develop and maintain py-spark scripts for automation of data processing tasks.
  • Implement full and incremental data loading strategies to ensure data consistency and availability.
  • Orchestrate and monitor workflows using Apache Airflow.
  • Ensure code quality and version control using GIT.
  • Troubleshoot and resolve data-related issues in a timely manner.
  • Stay up-to-date with the latest industry trends and technologies to continuously improve our data :
  • Proven experience as a Data Engineer (ETL, data warehousing, data Lakehouse).
  • Strong knowledge of Spark on Kubernetes, S3 and Docker Images.
  • Proficiency in Data engineering techniques with Py-spark.
  • Strong experience in Data warehousing techniques like data mining, data analysis, data profiling.
  • Experience with Python scripting for automation.
  • Expertise in full and incremental data loading techniques.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work collaboratively in a team environment and communicate effectively with stakeholders.
  • Good to have :

  • Understanding of streaming data applications using.
  • Hands-on experience with Apache Airflow for workflow orchestration.
  • Proficiency with GIT for version control
  • Understanding of data engineering integration with LLMs or GEN-AI applications and Vector DB.
  • Knowledge on Shell scripting Postgres SQL or SQL server or MSBI.
  • (ref : hirist.tech)

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