Job Description
<p><p><b>Description :</b><br/><br/>We are looking for a highly skilled Senior Data Engineer to join our data engineering team.<br/><br/>The ideal candidate will design, build, and optimize robust and scalable data pipelines and platforms to support our data analytics, reporting, and machine learning initiatives.<br/><br/>You will work closely with data scientists, analysts, and software engineers to ensure efficient data flow, high data quality, and availability across multiple systems.<br/><br/>This role requires strong expertise in modern data engineering tools, cloud platforms, and best practices for managing large-scale data infrastructures.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Design, develop, and maintain scalable and reliable data pipelines and ETL/ELT workflows for batch and real-time data processing.<br/><br/>- Architect and implement data ingestion, transformation, and storage solutions using cloud services (AWS, Azure, or GCP) and big data technologies.<br/><br/>- Build and manage data lakes, data warehouses, and data marts to enable efficient data analytics and business intelligence.<br/><br/>- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.<br/><br/>- Optimize data processing workflows to improve performance, reduce latency, and control costs.<br/><br/>- Implement data quality, validation, and monitoring frameworks to ensure accuracy and reliability.<br/><br/>- Develop and maintain documentation, including data dictionaries, pipeline architecture, and operational procedures.<br/><br/>- Enforce data governance, security, and compliance standards to protect sensitive information.<br/><br/>- Mentor junior data engineers and support continuous improvement of engineering practices.<br/><br/>- Stay updated with the latest trends and advancements in data engineering, cloud platforms, and big data ecosystems.<br/><br/><b>Required Skills & Experience :</b><br/><br/>- 5+ years of hands-on experience in data engineering or related roles.<br/><br/>- Strong proficiency in Python, SQL, and data processing frameworks such as Apache Spark, Flink, or Beam.<br/><br/>- Experience designing and implementing ETL/ELT pipelines using tools like Airflow, AWS Glue, Databricks, or similar orchestration platforms.<br/><br/>- Hands-on expertise with cloud platforms and services like AWS (S3, Redshift, EMR, Lambda), Azure Data Factory, Google Cloud Dataflow, or equivalent.<br/><br/>- Experience with data warehousing concepts and tools such as Snowflake, BigQuery, Redshift, or Azure Synapse Analytics.<br/><br/>- Familiarity with NoSQL and relational databases (e.g., MongoDB, Cassandra, PostgreSQL, MySQL).<br/><br/>- Strong understanding of data modeling, schema design, and database optimization.<br/><br/>- Experience with containerization (Docker) and orchestration (Kubernetes) is a plus.<br/><br/>- Knowledge of data governance, security best practices, and compliance standards (GDPR, HIPAA).<br/><br/>- Excellent problem-solving skills and ability to troubleshoot data issues in complex distributed environments.<br/><br/>- Strong communication and collaboration skills with experience working in Agile teams</p><br/></p> (ref:hirist.tech)