IT Lead Data Engineer

The Lead Data Engineer is responsible for leading in the designing, building, and maintaining of the systems and infrastructure that enable organizations to collect, store, process, and analyze large volumes of data. This role involves collaborating closely with data scientists, analysts, QA engineers, business process / functional SMEs, and other stakeholders to ensure that data is accessible, reliable, and secure. They are responsible for tasks such as data ingestion, data transformation, data integration, and data pipeline development. Lead Data Engineers also play a crucial part in data governance, ensuring that data is compliant with regulations and policies. This role also includes all aspects of software development and deployment of IT Operations to shorten delivery and time to market for data products and data pipelines and data warehousing. Overall, the incumbent helps organizations leverage their data to gain meaningful insights and make informed decisions.

Lead and manage a team of data engineers, providing technical guidance, mentorship, and support

Act as a Subject Matter expert for clients and stakeholders, providing updates and addressing any data related technical inquiries or concerns

Oversee and drive the design, development, and maintenance of efficient and robust data pipelines, ETL processes, and data workflows

Manage the development and maintenance of data models and schema designs to support data storage and retrieval needs

Optimize data storage, processing, and retrieval mechanisms for performance and scalability

Provide technical leadership and guidance in the selection and implementation of data engineering tools and technologies

Identify and implement best practices and standards for data engineering processes and tools

Stay up-to-date with emerging technologies and trends in data engineering, evaluating their potential impact on our data infrastructure

Lead the Collaboration with cross-functional teams to integrate data sources and enable seamless data flow across systems and with data scientists, analysts, and stakeholders to understand data requirements and develop scalable data solutions

Lead the implementation and maintenance of data governance and security measures to protect sensitive information and to ensure data quality and integrity by implementing effective data validation and cleansing techniques

This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H-1B visa.

This position is eligible to work in the office three days a week and has the option to work remotely two days a week.

Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company's staff, employees, and business relationships.

Education

Required

Bachelor's degree in Computer Science, Computer Engineering, or Information Technology or in lieu of a degree, at least 9 years of experience in data engineering.

Skills and Experience

Required

6-8+ years of data engineering experience.

4-6+ years of experience with SQL including, but not limited to: PostgreSQL, T-SQL, PL/SQL, SNOWSQL

4-6+ years of experience with building applications, system integrations, and web services

4-6+ years of experience with server-side scripting and programming in a Linux environment (primarily bash shell)

Experience with common database (Oracle, Snowflake) technologies including performance, tuning, and optimization.

Experience with data manipulation and on-prem and cloud-based data warehouse ETL tools and processes

Experience with business processes such as OTC, P2P,PIM to understand context of data usage

Technical Skills

Domain architecture

Data security

Automated testing tools

Version control tools

Data modeling

Preferred

6-8 years' experience with IDMC, programming languages like Python, Bash and SQL

4-6 years' experience with data engineering principles and Data Quality Principles

4-6 years' experience with Cloud Platforms like Azure and Snowflake

4-6 years' experience with Data Modeling/DataVault