Data Engineer
7 days ago
ResponsibilitiesDesign and implement data processing systems using distributed frameworks like Hadoop, Spark, Snowflake, Airflow, or other similar technologies.Build data pipelines to ingest data from various sources such as databases, APIs, or streaming platforms.Integrate and transform data to ensure its compatibility with the target data model or format.Design and optimize data storage architectures, including data lakes, data warehouses, or distributed file systems.Implement techniques like partitioning, compression, or indexing to optimize data storage and retrieval.Identify and resolve bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency.Design and implement data models that support efficient data storage, retrieval, and analysis.Collaborate with data scientists and analysts to understand their requirements and provide them with well-structured and optimized data for analysis and modeling purposes.Utilize frameworks like Hadoop or Spark to perform distributed computing tasks, such as parallel processing, distributed data processing, or machine learning algorithms.Implement security measures to protect sensitive data and ensuring compliance with data privacy regulations.Establish data governance practices to maintain data integrity, quality, and consistency.Monitor system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations.Communicating complex technical concepts to non-technical stakeholders in a clear and concise manner.Stay updated with emerging technologies, tools, and techniques in the field of big data engineering.What We're Looking For:Strong analytical thinking and problem-solving skillsStrong communication skillset – ability to translate technical details to business/non-technical stakeholdersExtensive experience in designing and building data pipelines (ELT/ETL) for large-scale datasets. Familiarity with tools like Databricks, Apache Nifi, Apache Airflow, or Informatica is advantageousProficiency in programming languages such as Python, R or Scala is essential.In-depth knowledge and experience with distributed systems and technologies, including On-prem Platforms, Apache Hadoop, Spark, Hive or similar frameworks. Familiarity with cloud-based platforms like AWS, Azure, or Google Cloud is highly desirable.Solid understanding of data processing techniques such as batch processing, real-time streaming, and data integration. Experience with data analytics tools and frameworks like Apache Kafka, Apache Flink, or Apache Storm is a plus.Experience with Azure Data Services - Databricks and Data FactoryExperience with Git repository maintenance and DevOps conceptsFamiliarity with building, testing, and deploying processAdditional certifications in big data technologies or cloud platforms are advantageousOther DetailsWork Setup: Hybrid (2x onsite per week) in BGC, Taguig Client (with allowance)Interview Process: Aspiree Phone Screening > HR Interview > Technical Interview > Hiring Manager InterviewJob Types: Full-time, PermanentAbility to commute/relocate:Taguig: Reliably commute or planning to relocate before starting work (Preferred)Application Question(s):Are you willing to work on a hybrid setup in BGC, Taguig?Education:Bachelor's (Preferred)Experience:data engineering: 8 years (Preferred)SQL: 5 years (Preferred)Azure cloud technologies: 5 years (Preferred)on-premises platforms: 5 years (Preferred)Work Location: In person
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