Associate Team Lead- Data Engineer

Devsinc; Lahore; On-site; PKR 2,500,000 - 4,500,000; Full time

Job summary

Devsinc, LLC is seeking an Associate Team Lead- Data Engineer to guide data pipelines, collaborate with cross-functional teams, and mentor junior engineers. You will architect scalable ETL processes and ensure data quality across cloud data services.

The role demands 4+ years in data engineering, strong SQL (PostgreSQL/MySQL), experience with Airflow or similar ETL tools, Python or Scala, and hands-on cloud platform experience (AWS/Azure/GCP).

Qualifications

• Bachelor’s degree in CS, data eng or related field.
• 4+ years in data engineering with pipelines experience.
• Strong SQL knowledge (PostgreSQL/MySQL).
• ETL tools: Airflow, Talend, AWS Glue.
• Python or Scala for data processing.
• Hands-on with AWS/Azure/GCP cloud data services.
• Understanding of data warehousing and Snowflake/Redshift.
• Excellent problem-solving and data integrity focus.
• Strong communication and collaboration skills.
• Proactive learner and team player.

Responsibilities

• Design, develop, and optimize scalable data pipelines and models for ETL.
• Collaborate with data scientists and stakeholders to define data requirements.
• Ensure data quality through validation and testing mechanisms.
• Leverage cloud data warehousing solutions to store and manage large datasets.
• Monitor production pipelines and resolve data availability issues.
• Contribute to data governance, security, and compliance practices.
• Stay current with industry trends and emerging data engineering technologies.

Skills

Communication

Problem-solving

Collaboration

Proactive learning

Education

Bachelor's degree in Computer Science, Data Engineering, or a related field

Tools

PostgreSQL

MySQL

Apache Airflow

Talend

AWS Glue

Python

Scala

AWS

Azure

GCP

Snowflake

Redshift

Job description

Job Description:

Devsinc is on the lookout for a highly motivated Associate Team Lead- Data Engineer to join our dynamic data team. In this pivotal role, you will be responsible for building and optimizing data pipelines that transform raw data into valuable insights and facilitate data-driven decision-making. Your ability to work collaboratively with cross-functional teams and your expertise in data engineering will play a key role in shaping our data architecture and ensuring the integrity and accessibility of our data.

Key Responsibilities:

• Design, develop, and enhance scalable data pipelines and data models to streamline the extraction, transformation, and loading (ETL) processes.
• Collaborate with data scientists, analysts, and stakeholders to define data requirements and deliver robust data solutions that align with business goals.
• Ensure data quality, consistency, and accuracy by implementing validation and testing mechanisms.
• Utilize cloud services and data warehousing solutions to efficiently store and manage large volumes of data.
• Monitor and troubleshoot production data pipelines, providing timely resolutions to issues affecting data availability.
• Contribute to data governance initiatives by enforcing best practices related to data security, privacy, and compliance.
• Stay updated with industry trends and emerging technologies in the data engineering space.

• Bachelor’s degree in Computer Science, Data Engineering, or a related field.
• 4+ years of experience in data engineering or a related role, with a proven track record in building data pipelines.
• Strong knowledge and experience in SQL and relational databases (e.g., PostgreSQL, MySQL).
• Familiarity with ETL tools and technologies (e.g., Apache Airflow, Talend, AWS Glue).
• Proficiency in programming languages such as Python or Scala for data processing.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data services.
• Understanding of data warehousing concepts and experience with data storage technologies (e.g., Snowflake, Redshift).
• Excellent problem-solving skills with a focus on data integrity and performance optimization.
• Strong communication skills, with the ability to convey technical concepts to non-technical stakeholders.
• A collaborative spirit, with a willingness to work closely with team members across various functions.
• A proactive approach to learning new tools and technologies in the data ecosystem.

Requirements: