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# AWS Databricks Consultant

- **Company:** J-ram It Consulting Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Agile Methodology, Amazon Web Services, Amazon S3, Computer Programming, Databases, Data Dictionary, Data Integration, Extract Transform Load (ETL), Data Mapping, Data Systems, Relational Databases, Python (Programming Language), Meta-Data Management, Microsoft SQL Server, Oracle (Applications), Query Optimization, Data Streaming, Data Ingestion, Apache Spark, Change Data Capture, Indexer, Pyspark, AWS Glue, Real Time Data, Api Gateway, Data Pipelines, Databricks
- **Published:** August 20, 2026
- **Apply:** https://www.dice.com/job-detail/e09c2ad4-9694-4b7d-8ab9-77837bab7c0a

## About the Role

Experience: 10 years Realtime experience on databricks is must.
Collaborate as part of a development team to design and enhance large scale applications developed using Python, Spark & Pyspark .
Realtime experience on databricks is must.
Evaluates and plans software designs, test results and technical manuals using AWS., At least 4+ years of experience on designing and developing Data Pipelines for Data Ingestion or Transformation using Scala or Python
At least 4 years of experience with Python, Spark & Pyspark
At least 3 years of experience working on AWS technologies.
Experience of designing, building, and deploying production-level data pipelines using tools from AWS Glue, Lamda, Kinesis using databases Aurora and Redshift.
Experience with Spark programming (pyspark or scala).
Hands on experience with AWS components like (EMR, S3, Redshift, Lamdba, API Gateway, Kinesis ) in production environments
Strong analytical skills and advanced SQL knowledge, indexing, query optimization techniques.
Experience using ETL tools for data ingestion.
Experience with Change Data Capture (CDC) technologies and relational databases such as MS SQL, Oracle and DB
Ability to translate data needs into detailed functional and technical designs for development, testing and implementation.

## Description

Confer with business units and development staff to understand both the business and technical requirements for producing technical solutions.
Create and review technical and user-focused documentation for data solutions (data models, data dictionaries, business glossaries, process and data flows, architecture diagrams, etc.).
Extend and enhance the business Data Lake
Create or implement solutions for metadata management
Solve for complex data integrations across multiple systems.
Design and execute strategies for real-time data analysis and decisioning. Build robust data processing pipelines using AWS Services and integrate with multiple data sources.
Translating client user requirements into data flows, data mapping, etc.
Analyses and determines data integration needs and follows Agile practices.


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