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Weekday AI (YC W21)
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Data Engineer

Data Engineer

Weekday AI (YC W21)

5 years

0 Lacs

hyderabad telangana india

Posted:19 hours ago| Platform:

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Skills Required

data engineering processing support software pipeline development design scala architecture apache spark kafka hadoop database management relational sql nosql storage retrieval accessibility etl test integration collaboration engagement optimization efficiency tuning monitoring governance checks programming api mongodb redshift aws azure gcp dataflow databricks strategies scalability git containerization docker kubernetes debugging learning security compliance

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of the Weekday's clients

Min Experience: 5 yearsLocation: HyderabadJobType: full-timeWe are seeking a highly skilled and motivated

Data Engineer

with strong expertise in

Scala

to join our data engineering team. The ideal candidate will bring 5-15 years of experience in designing, developing, and maintaining scalable data pipelines and distributed systems. This role requires a strong background in data engineering, deep knowledge of modern data platforms, and hands-on experience with large-scale data processing frameworks.As a Data Engineer, you will be responsible for building and optimizing data systems that support our analytical, operational, and business intelligence needs. You will collaborate closely with data scientists, analysts, and software engineers to ensure reliable, accurate, and accessible data across the organization.

Requirements

Key Responsibilities

Data Pipeline Development: Design, build, and optimize large-scale data pipelines using Scala to process structured, semi-structured, and unstructured data efficiently.
Data Architecture: Contribute to the design and implementation of robust, scalable, and high-performing data architectures that meet the evolving needs of the business.
Big Data Processing: Leverage distributed computing frameworks such as Apache Spark, Kafka, Flink, or Hadoop to process and manage high volumes of real-time and batch data.
Database Management: Work with relational (SQL) and non-relational databases (NoSQL, key-value stores, columnar databases) to ensure optimal storage, retrieval, and accessibility of data.
ETL & Data Transformation: Develop, test, and maintain efficient ETL processes for ingestion, transformation, and integration of data from multiple sources into centralized platforms.
Collaboration & Stakeholder Engagement: Partner with cross-functional teams—including analysts, product managers, and business stakeholders—to understand requirements and deliver data solutions that support decision-making.
Performance Optimization: Ensure high availability, fault tolerance, and efficiency in data systems by optimizing queries, tuning data pipelines, and implementing performance monitoring.
Data Quality & Governance: Implement best practices for data validation, quality checks, lineage, and governance to maintain reliable and trustworthy datasets.

Required Skills & Qualifications

Professional Experience: 5-15 years of proven experience as a Data Engineer or in a similar data-focused role.
Scala Expertise: Strong proficiency in Scala programming for data engineering applications.
Big Data Technologies: Hands-on experience with distributed data processing frameworks such as Apache Spark (Scala API preferred).
ETL Development: Expertise in building and managing data ingestion, transformation, and integration pipelines.
Databases: Strong knowledge of SQL and exposure to modern data stores such as Cassandra, MongoDB, HBase, or Redshift.
Cloud Platforms: Experience with AWS, Azure, or GCP for data engineering solutions (S3, EMR, Dataflow, Databricks, etc.).
Data Modeling: Solid understanding of data modeling, schema design, and partitioning strategies for performance and scalability.
Version Control & CI/CD: Familiarity with Git, CI/CD pipelines, and containerization (Docker, Kubernetes).
Problem-Solving Skills: Strong analytical and debugging abilities to tackle complex data challenges.

Preferred Qualifications

Experience working in a fast-paced product-based environment or large-scale enterprise data systems.
Familiarity with functional programming paradigms and best practices in Scala.
Exposure to machine learning pipelines or real-time streaming data applications.
Knowledge of data governance frameworks, security, and compliance (GDPR, HIPAA, etc.)

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Data Engineer