Senior Data Engineer- AWS & Realtime DataBricks_Onsite@Dallas,TX(Locals)
OpenKyber LLC
Dallas, TX, United States
1 day ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source
Tech stack
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)
+15 more
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
Job description
Onsite Availability: for Interviews any time between 2 to 5 PM CST from Tuesday to Friday Mandatory skills: AWS, Databricks, Python, Spark & Pyspark, * Experience: 6 to 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.
- Evaluates and plans software designs, test results and technical manuals using AWS.
- 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.
Requirements
- 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.
For applications and inquiries, contact:hirings@openkyber.com
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