Job Title: Lead Engineer
What will you do?
The Lead Engineer contributes to setting a clear vision and strategic direction for data governance initiatives. This involves understanding the long-term goals of the organization and aligning data governance strategies accordingly. Moreover, the incumbent plays a key role in motivating and inspiring the team to achieve high standards and embrace the data governance framework when engaging with various stakeholders across the Enterprise. Articulate complex data governance concepts in a way that is easily understood by various stakeholders, including technical teams and business users.
- Cross-functional collaboration: Fostering a collaborative environment where various departments work together towards common data governance goals. This includes IT, legal, compliance, and business units. Develop strong relationships with stakeholders across the Enterprise
- Analytical thinking: Ability to analyze complex problems, identify root causes, and develop effective solutions. This is crucial for addressing data governance challenges and improving data quality. Making informed and timely decisions, to keep data governance initiatives on track.
- Adaptability and flexibility: Be flexible and open to change, especially as new data governance technologies, regulations, and best practices emerge. Seek feedback to improve performance and effectiveness in projects.
- Project and resource management: Contribute to multiple data governance projects simultaneously, ensuring that they are completed on time and within budget. Efficiently allocate resources, to maximize the impact of data governance initiatives.
What do you need to succeed?
Must-have
- Undergraduate degree or higher, preferable in Computer Science, Engineering or Finance other quantitative discipline; minimum of 0 years of experience in a similar role.
- Deep understanding of both relational (SQL Server, Oracle) and non-relational databases (NoSQL, MongoDB). Advanced SQL Proficiency: Ability to write complex SQL queries, optimize performance, and manage large-scale data operations.
- Prior extensive experience with at least one of the tools like Apache Atlas, Informatica, Collibra, Talend, Alation, and other data lineage and governance platforms, especially prior experience in customization and integration: having demonstrated the ability to implement, configure, customize, and integrate these tools to fit organizational needs.
- Expertise in at least one ETL tools such as Informatica, Talend, Microsoft SSIS, and Apache NiFi.
- Data Integration Design: Designing robust data integration frameworks to ensure seamless data flow across systems.
- Having demonstrated advanced programming skills in Python, especially in data manipulation, automation, and analytics. Prior experience in Java/Scala for developing custom data processing solutions and integrations. Shell Scripting: Advanced shell scripting skills for automating administrative tasks and data processes.
- Hadoop/Spark: Expertise in using big data technologies like Hadoop and Apache Spark.
- Managing Metadata Repositories: Experience with setting up and managing metadata repositories.
- Implementing Standards: Familiarity with implementing metadata standards and frameworks to maintain data quality and governance.
Nice-to-have
- Cloud Platforms: Proficiency with AWS, Google Cloud, or Azure for scalable data storage, processing, and analytics solutions.
- ETL processes and tools: Understanding of ETL tools like Informatica, Talend, or Microsoft SSIS.
- Experience with setting up and managing metadata repositories; familiarity with implementing metadata standards and frameworks to maintain data quality and governance.
- Having prior experience supporting compliance and security protocols, ensuring data governance processes comply with GDPR, CCPA, and other data privacy laws.
- Basic understanding of NLP/GenAI, concept of embedding, and GraphDB and other popular NonSQL to model non-tabular data is a plus.