We are seeking a highly skilled and experienced Cloud Data Engineer proficient in Microsoft Azure and/or other cloud platform – AWS preferably as well as experience in modern data transformation tools like dbt and Databrick to join our dynamic team.
Tasks:
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Design and implement data pipelines and ETL workflows using Azure or AWS services (or relevant).
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Develop and maintain data warehousing solutions on AWS and Azure (or relevant).
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Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
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Build and maintain efficient, scalable, and reliable data architectures for analytics and reporting.
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Work closely with the data analytics team to optimize data storage, processing, and retrieval for reporting and analysis purposes.
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Implement data quality checks and data validation processes to ensure accuracy and consistency of the data.
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Maintain and update data documentation and data dictionaries.
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Troubleshoot and resolve data-related issues in a timely manner.
Requirements:
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Data Engineering Experience: Candidates should have a proven track record in data engineering with a strong focus on data pipeline development, data transformation, and data integration with a minimum of 4+ years of relevant work experience.
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Cloud Platform Experience: The primary requirement is expertise in Microsoft Azure. Candidates should be well-versed in various Azure services like Azure Data Factory, Azure Databricks, Azure SQL Data Warehouse, and Azure Data Lake Storage. Secondary experience with other cloud platforms (AWS or Google Cloud) is a significant advantage.
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ETL and Data Transformation: Candidates should have experience with ETL (Extract, Transform, Load) processes and data transformation techniques. Proficiency in using ETL tools and frameworks is a key requirement.
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Programming and Scripting: Strong programming skills are essential, particularly in languages like Python and SQL. Experience with other languages may also be beneficial.
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Database Systems: Familiarity with relational databases (e.g., SQL Server, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra) is often required.
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Big Data Technologies: Experience with big data technologies and frameworks like Hadoop, Spark, and Hive can be advantageous.
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Data Warehousing: Understanding of data warehousing concepts and experience with data warehousing platforms (e.g., Azure SQL Data Warehouse, Amazon Redshift) is valuable.
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Data Modeling: Proficiency in data modeling, schema design, and data architecture is typically expected.
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Version Control: Familiarity with version control systems (e.g., Git) and code repository management is often required.
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Data Governance: Knowledge of data governance, data quality, and data lineage concepts is a plus.
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Cloud Certifications: Certifications related to Microsoft Azure, AWS can be advantageous and demonstrate expertise in these platforms.
We offer:
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Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
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“Office as an option” model. You can choose to work remotely or in the office.
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Great Place to Work® certified employer.
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Flexibility regarding working hours and your preferred form of contract.
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Comprehensive online onboarding program with a “Buddy” from day 1.
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Cooperation with top-tier engineers and experts.
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Unlimited access to the Udemy learning platform from day 1.
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Certificate training programs. Lingarians earn 500+ technology certificates yearly.
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Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
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Grow as we grow as a company. 76% of our managers are internal promotions.
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A diverse, inclusive, and values-driven community.
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Autonomy to choose the way you work. We trust your ideas.
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Create our community together. Refer your friends to receive bonuses.
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Activities to support your well-being and health.
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Plenty of opportunities to donate to charities and support the environment.
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Modern office equipment. Purchased for you or available to borrow, depending on your location.
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