Brief job description

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Key Responsibilities:

Develop and maintain the backend infrastructure for the Data Lake, ensuring high availability, security, and scalability.

Design and implement data ingestion pipelines to efficiently load data from multiple sources into the Data Lake.

Develop and optimize ETL (Extract, Transform, Load) processes for data integration, transformation, and enrichment.

Implement data storage strategies and data partitioning for efficient retrieval and analysis.

Ensure data quality, consistency, and integrity across all data sources and destinations within the Data Lake environment.

Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and provide backend support for BI solutions.

Monitor and maintain the performance of the Data Lake backend, troubleshooting and resolving any issues.

Stay current with the latest trends and best practices in Data Lake and backend technologies to continuously improve the data architecture.
Qualifications:

Bachelor s degree in Computer Science, Information Technology, or related field.

3-5 years of experience in backend development for BI/Data Lake environments.

Strong experience with Data Lake technologies such as Azure Data Lake, AWS Lake Formation, or Hadoop.

Proficiency in scripting and programming languages like Python, Scala, or Java.

Experience with cloud platforms (AWS, Azure, or GCP) and data storage services (e.g., S3, Azure Blob Storage).

Expertise in building and optimizing ETL pipelines using tools like Apache Spark, Talend, Informatica, or Glue.

Strong SQL skills and experience with data warehousing solutions (e.g., Redshift, Snowflake, BigQuery).

Knowledge of data governance, security, and compliance best practices.
Preferred Skills:

Experience with big data tools such as Apache Kafka, Apache Hive, and Presto.

Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

Knowledge of CI/CD tools and practices for automated deployment and testing.

Understanding of real-time data processing and streaming technologies.
Key Competencies:

Strong analytical and problem-solving skills with attention to detail.

Excellent communication skills to work effectively with cross-functional teams.

Proactive, self-motivated, and a quick learner with a passion for data engineering.

Ability to work in a fast-paced environment and manage multiple priorities.

Bachelor s degree in Business, Marketing, or a related field. MBA is a plus.