A
Data Engineer
A
Data Engineer
AccentureThis job is no longer accepting applications
Job Description
Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : NA
Minimum 3 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and contribute to the overall data strategy, ensuring that the data architecture aligns with business objectives and supports analytical needs.
Roles & Responsibilities:
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : Databricks Unified Data Analytics Platform
Good to have skills : NA
Minimum 3 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and contribute to the overall data strategy, ensuring that the data architecture aligns with business objectives and supports analytical needs.
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 design and implementation of data models to support business intelligence initiatives.
- Collaborate with data scientists and analysts to understand data needs and provide necessary data solutions.
- Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform- Python, SQL, Nodejs, Redis, Mongodb, Javascript
- Experience with data integration tools and techniques.
- Strong understanding of ETL processes and data warehousing concepts.
- Familiarity with cloud platforms and services related to data storage and processing.
- Knowledge of programming languages such as Python or Scala for data manipulation.
- The candidate should have minimum 3 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.
More Info
Key Skills
Databricks Unified Data Analytics Platform
Data integration tools and techniques
Cloud platforms and services related to data storage and processing
ETL processes
About Company
Skills:
snowflake , S3, Kafka, TigerGraph, Neo4j, Python, AWS, Java, RDS, Scala, Emr, Sql, Spark, Databricks, Restful Apis, Kubernetes, Airflow, Hudi, Amazon Neptune, ClickHouse, Astronomer, MSK, Iceberg, EMR on EKS, Delta Lake, Athena
Skills:
Data Warehousing Concepts, Data Modelling, Snaplogic, Agile Methodology, Snowflake Data Warehouse, Unix commands and scripting
Skills:
data streaming , Data Modeling, AWS Glue, Kafka, Data Governance, Python, AWS, Data Transformation, Java, Scala, Sql, Devops, Gcp, Spark, Azure, Airflow, Data Ingestion, Automated Deployment Pipelines, Data Lakehouses, Flink, Parquet, Data Lakes, Data Hubs, Iceberg, dbt, CI/CD
Skills:
Deduplication, Sql, Python, Ocr, Vector databases, Layout parsing, Batch and streaming pipelines, Classical extraction methods, Schema checks, anomaly detection, LLM evaluation sets, Human-in-the-loop review workflows, Document AI, Vector store indexing, LLM APIs, Embedding pipelines, AI agents, RAG pipelines, Multimodal models, Table extraction, Prompt design, Data quality validation
Skills:
RAG (Retrieval-Augmented Generation), Azure Data Factory (ADF), Pyspark, Azure Sql, Sql, ELT, Devops, Azure Synapse Analytics, Azure Data Lake, Spark, Cosmos DB, Python, Etl, Fabric Lakehouse architectures, Infrastructure as Code, vector databases, CI/CD pipelines, Microsoft Fabric, Azure AI Search