Lead Data Engineer
Posted on :
08-11-2023
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Job Description
As a Lead Data Engineer, you will lead the design and implementation of complex data solutions and manage the organization's data infrastructure. You will work closely with data scientists, analysts, and other engineers to ensure data is processed, stored, and analyzed efficiently and accurately. You must have extensive technical skills and experience designing and implementing large-scale data solutions.
Key Accountabilities
•Lead the design and implementation of complex data pipelines, ETL processes, and data warehousing solutions.
•Build and manage databases and data models.
•Develop and implement data integration and data transformation processes.
•Collaborate with data scientists and data analysts to understand data requirements and provide data in the required format.
•Ensure data accuracy, completeness, and integrity.
•Optimize system performance and recommend improvements to optimize performance.
•Implement and maintain data security measures.
•Ensure compliance with data privacy and data governance policies.
•Lead and mentor junior data engineers and provide technical guidance and support.
•Evaluate new data technologies and make recommendations for implementation.
•Manage projects and ensure timely delivery of data solutions.
Education, Experience, & Skill Requirements
•7-9 years of experience in data engineering, data warehousing, and ETL processes.
•Proficient in programming languages such as Python, Java, or SQL.
•Extensive experience with database technologies such as MySQL, PostgreSQL, or MongoDB.
•Experience with data visualization tools such as Tableau or Power BI.
•Experience with big data technologies such as Hadoop, Spark, or Kafka.
Key Metrics
•Understanding of data privacy and data governance policies.
•Strong problem-solving and analytical skills.
•Ability to work collaboratively in a team environment.
•Strong communication and interpersonal skills.
•Ability to lead and manage projects.
Additional Job Description
Key Accountabilities
•Lead the design and implementation of complex data pipelines, ETL processes, and data warehousing solutions.
•Build and manage databases and data models.
•Develop and implement data integration and data transformation processes.
•Collaborate with data scientists and data analysts to understand data requirements and provide data in the required format.
•Ensure data accuracy, completeness, and integrity.
•Optimize system performance and recommend improvements to optimize performance.
•Implement and maintain data security measures.
•Ensure compliance with data privacy and data governance policies.
•Lead and mentor junior data engineers and provide technical guidance and support.
•Evaluate new data technologies and make recommendations for implementation.
•Manage projects and ensure timely delivery of data solutions.
Education, Experience, & Skill Requirements
•7-9 years of experience in data engineering, data warehousing, and ETL processes.
•Proficient in programming languages such as Python, Java, or SQL.
•Extensive experience with database technologies such as MySQL, PostgreSQL, or MongoDB.
•Experience with data visualization tools such as Tableau or Power BI.
•Experience with big data technologies such as Hadoop, Spark, or Kafka.
Key Metrics
•Understanding of data privacy and data governance policies.
•Strong problem-solving and analytical skills.
•Ability to work collaboratively in a team environment.
•Strong communication and interpersonal skills.
•Ability to lead and manage projects.
Additional Job Description
-
- Responsible for designing solutions and working with conventional data warehouse technologies to develop models that best support a business or organization.
- Have hands-on experience planning, developing, and performing data extraction from various source systems and building data warehouses and data marts in relational databases while ensuring data integrity.
- Participate in Data Services agile team; recommend and implement changes to mitigate risks and optimize performance.
- Apply subject matter expertise to acquire and understand data integration requirements and deliver enterprise services to support business objectives.
- 2 + years of experience with cloud-native data stores (e.g., S3, Redshift, Snowflake), automation, and orchestration tools.
- Must have hands-on experience in warehouse tools like SAP BW on HANA, Enterprise HANA, Snowflake, Oracle DB, SQL Server, IBM DB2, Amazon Redshift, MS Azure, etc.
- Good to have exposure to SAP S/4 HANA finance.
- Good to have exposure to General Ledger, Asset Accounting, Accounts payable and receivables, Cash Management, Cost Center Accounting, Profit Center Accounting, and Internal Orders.
- Must have hands-on experience in enterprise or cloud-based ETL tools like Informatica, SAP data Service, Talend, Azure Data Factory, Data Stage, SAS, etc.
- Good to have AWS or Azure cloud certification.
Employment Type
Full Time
Key Skills
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