Data Engineer

SRS Consulting Inc

United States

21 days ago

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

www.dice.com

Tech stack

Sql Data Warehouse Application Programming Interfaces (APIs) Agile Methodology Amazon Web Services Amazon S3 Batch Processing Big Data Cloud Computing Information Systems Databases Continuous Integration Information Engineering

+30 more

Data Integration Extract Transform Load (ETL) Data Warehousing DevOps JSON Python (Programming Language) MongoDB NoSQL Cloud Services Simple Data Format SQL Databases Data Streaming Unstructured Data Jupyter Notebook Parquet Data Processing Google Cloud Data Ingestion Delivery Pipeline Snowflake Git Cloudformation Pandas Information Technology Avro Functional Programming Amazon Simple Queue Service (SQS) Terraform Software Version Control Data Pipelines

Requirements

USA experience: 4 6 Years

Bachelor’s or master s degree in Computer Science, Information Systems, or related field

Design data pipelines for API, streaming, and batch processing to facilitate data loads into the Snowflake data warehouse.
Collaborate with other engineering and DevOps team members to implement, test, deploy, and operate data pipelines and ETL solutions.
Develop scripts to Extract, Load and Transform data and other utility functions
Optimize data pipelines, ETL processes, and data integrations for large-scale data analytics use cases
Build necessary components to ensure data quality, monitoring, alerting, integrity, and governance standards are maintained in data processing workflows
Able to navigate ambiguity and thrives in a fast-paced environment. Takes initiative and consistently delivers results with minimal supervision.
7+ years of experience in building and maintaining data pipelines and ETL/ELT processes in data-centric organizations
Strong coding skills using Python. Familiar with Python libraries related to data engineering and cloud services including pandas, boto, etc.
At least 3 years of experience with AWS S3, SQS, Kinesis, Lambda, AWS DMS, Glue/EMR, AWS Batch or similar services.
Hands-on experience building streaming and batch big data data pipelines
Must have knowledge of building Infrastructure in AWS cloud using Cloud formation or Terraform
Experience on Anakonda and Jupyter Notebook
3+ years of working experience with Snowflake cloud data warehouse including Snowflake data shares, Snowpipes, Snow SQL, Tasks etc
Must have working knowledge of various databases, SQL and NoSQL
Must have working knowledge of various file formats like CSV, Json Avro, and Parquet.
Hands-on experience with cloud platforms such as AWS and Google Cloud.
Experience working with agile development methodology.
Experienced in CI/CD and release processes, proficient in Git or other source control management systems, to streamline development and deployment workflows

Other Desired Skills:

Minimum 5 years of designing and implementing operational production grade large-scale data pipelines, ETL/ELT and data integration solutions.
Exposure to multi-tenant/multi-customer environments is a big plus.
Hands on experience with productionized data ingestion and processing pipelines
Strong understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologies.
Experience working with structured, semi-structured, and unstructured data.
Familiarity with MongoDB or similar NoSQL database systems.