Provide leadership and guidance to the data engineering team, including mentoring, coaching, and fostering a collaborative work environment. Set clear goals, assign tasks, and manage resources to ensure successful project delivery. Work closely with developers to support them and improve data engineering processes.
Support team members with troubleshooting and resolving complex technical issues and challenges.
Provide technical expertise and direction in data engineering, guiding the team in selecting appropriate tools, technologies, and methodologies. Stay updated with the latest advancements in data engineering and ensure the team follows best practices and industry standards.
Collaborate with stakeholders to understand project requirements, define scope, and create project plans.
Support project managers to ensure that projects are executed effectively, meeting timelines, budgets, and quality standards. Monitor progress, identify risks, and implement mitigation strategies.
Act as a trusted advisor for the customer.
Oversee the design and architecture of data solutions, collaborating with data architects and other stakeholders. Ensure data solutions are scalable, efficient, and aligned with business requirements. Provide guidance in areas such as data modeling, database design, and data integration.
Align coding standards, conduct code reviews to ensure proper code quality level.
Identify and introduce quality assurance processes for data pipelines and workflows.
Optimize data processing and storage for performance, efficiency and cost savings.
Evaluate and implement new technologies to improve data engineering processes on various aspects (CICD, Quality Assurance, Coding standards).
Act as main point of contact to other teams/contributors engaged in the project.
Maintain technical documentation of the project, control validity and perform regular reviews of it.
Ensure compliance with security standards and regulations.
A bachelors or masters degree in Computer Science, Information Systems, or a related field is typically required. Additional certifications in cloud are advantageous.
Minimum of 5 years of experience in data engineering or a related field.
Strong technical skills in data engineering, including proficiency in programming languages such as Python, SQL, Pyspark.
Experience in profiling tool such as Pandas.
Familiarity with Azure cloud platform viz. Azure Databricks, Data Factory, Data Lake, Azure SQL etc., and experience in implementing data solutions in a cloud environment.
Expertise in working with various data tools and technologies, such as ETL frameworks, data pipelines, and data warehousing solutions.
Proven experience in leading and managing a team of data engineers, providing guidance, mentorship, and technical support.
In-depth knowledge of data management principles and best practices, including data governance, data quality, and data integration.
Strong project management skills, with the ability to prioritize tasks, manage timelines, and deliver high-quality results within designated deadlines.
Excellent problem-solving and analytical skills, with the ability to identify and resolve complex data engineering issues.
Knowledge of data security and privacy regulations, and the ability to ensure compliance within data engineering projects.
Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams, stakeholders, and senior management.
Continuous learning mindset, staying updated with the latest advancements and trends in data engineering and related technologies.
