3+ years of experience in a data-focused role (Data Scientist, Data Analyst, Business Intelligence).
Strong command of SQL with experience writing optimized queries (joins, aggregations, filters, CTEs).
Proven experience in data cleaning, transformation, and ETL/ELT workflows.
Experience using Databricks or similar platforms for data processing, notebooks, or workflow management.
Experience building dashboards using tools like Metabase, Tableau, Looker, or Power BI.
Ability to create clear and intuitive dashboards for non-technical stakeholders.
Strong analytical thinking, with the ability to translate data into insights and insights into actionable recommendations.
Excellent communication skills, with the ability to explain complex findings in a simple and clear manner.
Highly organized, detail-oriented, and capable of managing multiple projects concurrently.
Proactive and comfortable working in a dynamic, fast-paced environment.
Experience with machine learning techniques (regression, classification, clustering, forecasting).
Familiarity with Python or R for data analysis, modeling, or automation.
Exposure to SaaS or healthcare datasets.
Experience working with large datasets or cloud data warehouses (Snowflake, BigQuery, Redshift).
Experience with data governance, metadata management, or setting up data catalogs

Define, manage, and optimize the data pipeline, ingestion from internal systems, external sources, APIs, etc.
Clean, validate, and transform raw data to prepare it for analysis and reporting.
Conduct exploratory data analysis to identify trends, patterns, anomalies, and business opportunities.
Write efficient SQL queries to extract data, build metrics, and support business decisions.
Build dashboards, visualizations, and automated reports for cross-functional teams.
Collaborate with product, engineering, operations, and leadership to understand data needs and provide actionable insights.
Monitor data quality, integrity, and performance; proactively detect and resolve issues.
Maintain documentation for datasets, definitions, dashboards, and key metrics.
Promote a data-driven culture by enabling teams to use data confidently and effectively.
Continuously evaluate and recommend improvements to the Companys data tools, architecture, and processes.

03:00 PM - 12 AM

3+ years of experience in a data-focused role (Data Scientist, Data Analyst, Business Intelligence).
Strong command of SQL with experience writing optimized queries (joins, aggregations, filters, CTEs).
Proven experience in data cleaning, transformation, and ETL/ELT workflows.
Experience using Databricks or similar platforms for data processing, notebooks, or workflow management.
Experience building dashboards using tools like Metabase, Tableau, Looker, or Power BI.
Ability to create clear and intuitive dashboards for non-technical stakeholders.
Strong analytical thinking, with the ability to translate data into insights and insights into actionable recommendations.
Excellent communication skills, with the ability to explain complex findings in a simple and clear manner.
Highly organized, detail-oriented, and capable of managing multiple projects concurrently.
Proactive and comfortable working in a dynamic, fast-paced environment.
Experience with machine learning techniques (regression, classification, clustering, forecasting).
Familiarity with Python or R for data analysis, modeling, or automation.
Exposure to SaaS or healthcare datasets.
Experience working with large datasets or cloud data warehouses (Snowflake, BigQuery, Redshift).
Experience with data governance, metadata management, or setting up data catalogs

Define, manage, and optimize the data pipeline, ingestion from internal systems, external sources, APIs, etc.
Clean, validate, and transform raw data to prepare it for analysis and reporting.
Conduct exploratory data analysis to identify trends, patterns, anomalies, and business opportunities.
Write efficient SQL queries to extract data, build metrics, and support business decisions.
Build dashboards, visualizations, and automated reports for cross-functional teams.
Collaborate with product, engineering, operations, and leadership to understand data needs and provide actionable insights.
Monitor data quality, integrity, and performance; proactively detect and resolve issues.
Maintain documentation for datasets, definitions, dashboards, and key metrics.
Promote a data-driven culture by enabling teams to use data confidently and effectively.
Continuously evaluate and recommend improvements to the Companys data tools, architecture, and processes.

03:00 PM - 12 AM

Data Engineer (Onsite, Evening Shift, Lahore, PKR Salary)

Skills