Data Engineer
iSpace Inc
New York, NY, United States
14 days ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source
Tech stack
Agile Methodology
Airflow
Amazon Web Services
Amazon Elastic Compute Cloud
Amazon S3
Data Analysis
Big Data
Computer Programming
Computer Engineering
Continuous Integration
Information Engineering
Data Mapping
+40 more
Data Warehousing
Decision Support Systems
Software Design Patterns
Dimensional Modeling
Distributed Computing Environment
Amazon DynamoDB
Github
Revision Control Systems
Apache Hadoop
Python (Programming Language)
Key Management
NoSQL
Operational Databases
Performance Tuning
Unstructured Data
System Availability
Snowflake
Apache Spark
Software Application Programming
Electronic Medical Records
Amazon Relational Database Service
Pyspark
Integration Tests
Information Technology
Low Latency
Apache Flink
No-code Tools
Low-code
Real Time Data
Apache Kafka
Bitbucket
Data Management
Functional Programming
Api Design
Stream Processing
Data Pipelines
Sql Tuning
Serverless Computing
Jenkins
Amazon Redshift
Job description
Looking for Senior Data Engineer with a passion for building robust, scalable, efficient, and high-quality Data Engineering solutions to join our Engineering team. If you enjoy designing and building innovative data engineering solutions using the latest tech stack in a fast-paced environment, this role is for you. Primary Job Duties and Responsibilities
- Collaborate with and across Agile teams to design and develop data engineering solutions by rapidly delivering value to our customers.
- Build distributed, low latency, reliable data pipelines ensuring high availability and timely delivery of data
- Design and develop highly optimized data engineering solutions for Big Data workloads to efficiently handle continuous increase in data volume and complexity
- Build highly performing real-time data ingestion solutions for streaming workloads.
- Adhere to best practices and agreed upon design patterns across all Data Engineering solutions
- Ensure the code is elegantly designed, efficiently coded, and effectively tuned for performance
- Focus on data quality and consistency, implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
- Create design (Data Flow Diagrams, Technical Design Specs, Source to Target Mapping documents) and test (unit/integration tests) documentation
- Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
- Focus on end-to-end automation of data engineering pipelines and data validations (audit, balance controls) without any manual intervention
- Focus on data security and privacy by implementing proper access controls, key management, and encryption techniques.
- Take a proactive approach in learning new technologies, stay on top of tech trends, experimenting with new tools & technologies and educate other team members.
- Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility, and fostering data-driven decision making across the organization.
- Communicate clearly and effectively to technical and non-technical leadership.
Requirements
- Education: Bachelor’s degree in Computer Science, Computer Engineering, or relevant field
- Work Experience: 7+ years of experience in architecting, designing and building Data Engineering solutions and Data Platforms
- Experience in building Data Warehouses/Data Platforms on Redshift/Snowflake
- Extensive experience building real-time data processing solutions.
- Extensive experience building highly optimized data pipelines and data models for big data processing.
- Experience working with data acquisition and transformation tools such as Fivetran and DBT
- Experience building highly optimized & efficient data engineering pipelines using Python, PySpark, Snowpark
- Experience working with distributed data processing frameworks such as Apache Hadoop, or Apache Spark or Flink
- Experience working with real-time data streams processing using Apache Kafka, Kinesis or Flink
- Experience working with various AWS Services (S3, EC2, EMR, Lambda, RDS, DynamoDB, Redshift, Glue Catalog)
- Expertise in Advanced SQL programming and SQL Performance Tuning
- Experience with version control tools such as GitHub or Bitbucket.
- Expert level understanding of dimensional modeling techniques
- Excellent communication, adaptability, and collaboration skills
- Excellent analytical skills, strong attention to detail with emphasis on accuracy, consistency, and quality
- Strong logical and problem-solving skills with critical thinking
Good to Have:
- Experience in designing and building applications using Container and serverless technologies
- Experience working with fully automated workflow scheduling and orchestration services such as Apache Airflow
- Experience working with semi-structured, unstructured data, No SQL databases
- Experience with CI/CD using GitHub Actions or Jenkins
- Experience designing and building APIs
- Experience working with low-code, no-code platforms
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