Company
AI & Data Engineering : Data Engineering
LeadDataEngineer
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Data Engineer. Skills: Data Engineering, ETL, Data Architecture, SQL, Python, Data Warehousing, Data Modelling, Spark, AWS. building batch and real-time data pipelines. writing complex Python modules for custom ETL workflows”
Industry & Context.
What They're Looking For.
Must Have
experience in data engineering, ETL, data architecture, SQL skills, writing complex Python modules for custom ETL workflows, building batch and real-time data pipelines, understanding of data modeling, data warehousing, big data processing, data quality, monitoring, pipeline orchestration frameworks
Nice to Have
Informatica, Salesforce platforms and data models, Airflow, MuleSoft, Snowflake, dbt for data transformation and modeling, AWS/GCP, distributed/event-driven architectures, Salesforce Flows and Apex, Agile delivery process
What You'll Do.
building batch and real-time data pipelines
writing complex Python modules for custom ETL workflows
How You'll Work.
Team & Collaboration
Ability to work closely with Product, Data Science, and Analytics teams
Full Job Description
## Description Lead Data Engineer ## Primary Skills Athena, Step Functions, Spark - Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Data Modelling Fundamentals, Cloud front ## Specialization AWS Data EngineerIng Basic: Senior Data Engineer ## Job requirements Strong experience in data engineering, ETL (preferably Informatica), and data architecture ● Experience working with Salesforce platforms and data models ● Hands-on experience with Airflow and MuleSoft ● Strong SQL skills with Snowflake and other relational databases ● Experience writing complex Python modules for custom ETL workflows ● Expertise in building batch and real-time data pipelines ● Experience with dbt for data transformation and modeling ● Familiarity with AWS/GCP and distributed/event-driven architectures ● Strong understanding of data modeling, data warehousing, and big data processing ● Experience with data quality, monitoring, and pipeline orchestration frameworks ● Ability to work closely with Product, Data Science, and Analytics teams ● Experience working on Salesforce Flows and Apex is a plus ● Good understanding of Agile delivery process
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