About Data Engineering:
Data engineering involves the development of solutions for the collection, transformation, storage and management of data to support data-driven decision making and enable efficient data analysis by end users. It focuses on the technical aspects of data processing, integration, and delivery to ensure that data is accurate, reliable, and accessible in a timely manner. It also focuses on the scalability, cost-effectiveness, security, and supportability of the solution. Data engineering encompasses multiple toolsets and architectural concepts across on-premises and cloud stacks, including but not limited to data warehousing, data lakes, lake house, data mesh, and includes extraction, ingestion, and synchronization of structured and unstructured data across the data ecosystem. It also includes processing organization and orchestration, as well as performance optimization of data processing.
Duties
- 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.
- 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).
- Maintain technical documentation of the project, control validity and perform regular reviews of it.
- Ensure compliance with security standards and regulations.
Requirements:
- A bachelor's or master’s degree in computer science, Information Systems, or a related field is typically required. Additional certifications in cloud are advantageous.
- Minimum of 4 years of experience in data engineering or a related field.
- Candidate should be able to work in US shift timing (7:30 PM IST to 3:30 AM IST)
Must have:
- ETL Tools, including Azure Data Factory, Azure Databricks, Data Lake - implementing data ingestion pipelines from multiple data sources
- Databricks/Spark development
- Very good knowledge of cloud data services, data warehousing, big data technologies, and data lakes. Especially Azure, DataBricks
- SQL - designing, building, and managing SQL Server databases in the Azure cloud
- Programming skills for data analysis (especially PySpark, SparkSQL, Python, SQL).
- Understanding of data visualization tools (e.g., Power BI)
Why join us:
- Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
- 100% remote.
- Flexibility regarding working hours.
- Full-time position
- Comprehensive online onboarding program with a “Buddy” from day 1.
- Cooperation with top-tier engineers and experts.
- Unlimited access to the Udemy learning platform from day 1.
- Certificate training programs. Lingarians earn 500+ technology certificates yearly.
- Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
- Grow as we grow as a company. 76% of our managers are internal promotions.
- A diverse, inclusive, and values-driven community.
- Autonomy to choose the way you work. We trust your ideas.
- Create our community together. Refer your friends to receive bonuses.
- Activities to support your well-being and health.
- Plenty of opportunities to donate to charities and support the environment.