Data Engineer (Onsite, Lahore, PKR Salary)

Responsibilities:

• Design, build, and maintain robust and scalable ETL (Extract, Transform, Load) pipelines for collecting, processing, and transforming large datasets.
• Implement, configure, and optimize database architectures, including relational (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra) databases.
• Monitor database performance, troubleshoot issues, and tune SQL queries for optimal efficiency.
• Ensure data integrity, accuracy, and consistency across all database systems through regular maintenance and performance checks.
• Integrate data from various sources (APIs, flat files, streaming, etc.) to create a unified and efficient data ecosystem.
• Automate database backup, restoration, and recovery operations to ensure data availability.
• Develop and maintain data warehouse solutions to support analytics, reporting, and business intelligence needs.
• Implement data governance policies to manage data security, privacy, and compliance across all systems.
• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver tailored solutions that align with business objectives.
• Automate manual processes for data extraction and transformation, and optimize data pipelines for performance and scalability.
• Implement database replication, archiving, and table partitioning strategies to enhance performance and manageability.
• Maintain detailed technical documentation on data architectures, data flows, database configurations, and system processes.
• Identify and resolve database-related issues and performance bottlenecks, providing technical support to application developers and users as needed.

Requirements:

• Minimum 5-7 years of proven experience as a Data Engineer with DBA expertise.
• Hands-on experience in building and managing ETL processes and data pipelines.
• Familiarity with big data tools such as Hadoop, Spark, or Kafka.
• Experience with cloud platforms (AWS, Azure, or GCP) for data storage and processing.
• Strong knowledge of data visualization tools such as Power BI, Power Apps, or Tableau.
• Proficient in SQL, R, Python, and other data-processing languages.
• Strong knowledge of database management, including relational (MySQL, PostgreSQL, etc.) and NoSQL databases (MongoDB, Cassandra).
• Familiarity with database backup and recovery strategies, security practices, and compliance regulations.
• DB replications, archiving, table partitioning, RDS, Unix, and DBMS
• Experience with data warehousing solutions like Amazon Redshift, Google BigQuery, or Snowflake.
• Knowledge of data modeling, schema design, and data versioning.
• Experience with workflow automation tools like Airflow or Luigi.