Data Engineer (ETL/Data Warehouse/Python)

The ideal candidate must have at least 10+ years of industry experience. He or she must be responsible for successful technical delivery of Data Warehousing and Business Intelligence projects.

Responsibilities

• Data extraction, Data cleaning, Data Loading, Statistical Data Analysis, Exploratory
  Data Analysis, Data Wrangling,
• Write complex SQL queries and stored procedures to extract, manipulate, and analyze data from
  relational databases
• Conduct diagnostic, troubleshooting steps and present conclusions to a varied audience
• comfortable slinging some code to solve a problem
• Build Data Marts and Data warehouses to facilitate analytical capabilities across the varied sources of data
• Design and implement data patterns on cloud using cloud Data warehouse and data virtualization tools
• Evaluate new tools and technologies for target state on cloud
• Learn and implement new ETL, BI tools and data warehousing technologies

Qualifications

• Senior Data professional with over 10 years of expertise in Data Engineering, Data Analysis, and Data
  Science.
• Experience creating Data Marts, Data warehouses on-premise and on cloud for real time and batch processing frameworks
• Experience building and optimizing big-data data pipelines and data sets including Postgres, AWS Relational Data Service
• extensive hands-on experience building and optimizing data structures for data analytics, data science and business intelligence
• Experience working AWS Glue jobs, pySpark to create ELT process.
• Experience building self-service data consumption patterns and knowledge of cloud-based data Lake platforms
• Experience wrangling data (structured and unstructured), in-depth knowledge of database architecture
• Experience utilizing or leading implementations leveraging ETL tools (Informatica / Talend), BI Reporting tools such as MicroStrategy, Microsoft Power BI, data modeling tools such as Erwin, Oracle, SQL server, NoSQL, JDBC, UNIX shell scripting, PERL and JAVA, XML/JSON files, SAS , Python, AWS cloud-native technologies, S3, Athena, Redshift
• Experience in snowflake is an added bonus.
• Familiarity with the following technologies: Hadoop, Kafka, Airflow, Hive, Presto, Athena, S3, Aurora, EMR, Spark
• Ability to drive, contribute to, and communicate solutions to technical product challenges
• Ability to roll-up your sleeves and work in process or resource gaps and fill it in yourself
• Excellent written and oral communication skills in English

Education

Bachelor s degree in computer science, Data Analytics, Information Systems, or a related degree or equivalent experience. Master s degree is preferred.