Lead Data Engineer

Devsinc is on the lookout for a highly motivated Lead Data Engineer to join our dynamic data team.
In this pivotal role, you will be responsible for building and optimizing data pipelines that transform raw data into valuable insights and facilitate data-driven decision-making.
Your ability to work collaboratively with cross-functional teams and your expertise in data engineering will play a key role in shaping our data architecture and ensuring the integrity and accessibility of our data.
Key Responsibilities: Design, develop, and enhance scalable data pipelines and data models to streamline the extraction, transformation, and loading (ETL) processes.
Collaborate with data scientists, analysts, and stakeholders to define data requirements and deliver robust data solutions that align with business goals.
Ensure data quality, consistency, and accuracy by implementing validation and testing mechanisms.
Utilize cloud services and data warehousing solutions to efficiently store and manage large volumes of data.
Monitor and troubleshoot production data pipelines, providing timely resolutions to issues affecting data availability.
Contribute to data governance initiatives by enforcing best practices related to data security, privacy, and compliance.
Stay updated with industry trends and emerging technologies in the data engineering space.
Bachelor’s degree in Computer Science, Data Engineering, or a related field.
4+ years of experience in data engineering or a related role, with a proven track record in building data pipelines.
Strong knowledge and experience in SQL and relational databases (e.
g., PostgreSQL, MySQL).
Familiarity with ETL tools and technologies (e.
g., Apache Airflow, Talend, AWS Glue).
Proficiency in programming languages such as Python or Scala for data processing.
Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data services.
Understanding of data warehousing concepts and experience with data storage technologies (e.
g., Snowflake, Redshift).
Excellent problem-solving skills with a focus on data integrity and performance optimization.
Strong communication skills, with the ability to convey technical concepts to non-technical stakeholders.
A collaborative spirit, with a willingness to work closely with team members across various functions.
A proactive approach to learning new tools and technologies in the data ecosystem.